Author: Awareness News

QAnon, the far-right conspiracy taking over the mainstream

January 7, 2021February 9, 2021by Awareness NewsLeave a comment

The Storm is Here

Human Beings love a good story, we crave for narratives that breakdown and explain information in a way we find compelling, sometimes in ways which confirm our own biases. Battles of existential good and evil have long been effective narratives to capture humanity’s attention, from religious myth to sci-fi blockbusters.

QAnon is in a way no different than a typical good versus evil type of story. It has roots in the Pizzagate conspiracy theory, which refers to several stories that circulated around the internet alleging that Hilary Clinton and top Democrats were part of a paedophilia ring, that held satanic rituals from the basement of a pizza restaurant in Washington D.C.. Later in October 2017, a user by the name Q started posting on 4chan, commenting on a cryptic statement by Donald Trump, “The calm before the storm”.

The storm in question? A supposed culmination of a battle between evil and good in which the good, will finally triumph defeating thousands of members of the “Cabal”, a group of powerful elites involved in paedophilia and focused on destroying the US, by arresting and executing them or, if they are lucky, sending them to Guantanamo Bay. This was the beginning of a growing internet community that spread theories about a cabal of satanic paedophilic politicians, celebrities and media figures that control the world.

The “Q” is a reference to Q-clearance – the maximum level of access to secret documents in the US government. Several posters on Q boards claim to be government insiders, some in the FBI and CIA, and thus having access to relevant information regarding the conspiracy.

Our Lord and Saviour Donald Trump

There is an intimate connection between QAnon and politics. Every good story needs a hero, a protagonist, in this case it is the current President Donald Trump, who acts as a messianic figure in the conspiracy mythology. He is the saviour of the United States, the one who will stop the Cabal and finally usher a time of peace and prosperity, free of paedophilia, illegal migrants, and supposed Islamic invasions. QAnon supporters study the Presidents words carefully hoping to spot coded language possibly related to this secret mission. For example, in a meeting regarding the North Korea nuclear programme, Donald Trump referred to a “Calm before the storm”, which was interpreted as a “stand-by” kind of comment.

QAnon has slowly infiltrated the political discourse and slid its way into national politics. Signs of support for the conspiracy became common in Trump rallies and republican events after 2018. In the 2020 elections, 27 candidates for the House of Representatives (25 republican and 2 independent) reportedly believed in QAnon, two of which were elected.

The conspiracy, except for some specific mythology and coded language, seems to share many of the common tropes of the far-right: paedophilia, Islamic invasion, an anti-system sentiment, and a deep distrust of institutions. Consequently, such movements tend to exhibit huge flexibility and adaptability to any new narrative that becomes relevant, for example, COVID scepticism.

QAnon goes international

QAnon Flag being waved at a Anti-Lockdown protest in Berlin

As QAnon grows, so does its Geographical outreach, which found fertile ground within European conspiracy theorists and far-right movements. The Coronavirus Crisis has been a catalyst for the spread of QAnon, having the Q signs appeared in protests over Coronavirus’ restrictions in Germany, Britain, France, Spain, and Portugal.

With the international expansion, QAnon lost its attachment to American politics, and it has adapted its language and narratives to better fit the different international realities. Earlier this year, in Germany (largest QAnon community besides the English-speaking countries), a large-scale joint NATO’s exercise was perceived as an attack, by Donald Trump, to free the German people from the control of the “deep state”. When the exercise was re-scaled this spring due to COVID, it was theorized that Merkel had created this “fake pandemic” to end the liberation plan.

Merkel has become an especially nefarious QAnon character, as her support for refugees led Merkel to be branded as a puppet of the global elite. The community attacks to her range from accusations of being a “Zionist Jew”, part of the Rothchild family, or even the granddaughter of Adolf Hitler.

Social media

With Trump rising in 2016, the expression “fake news” became widespread, and it was popularized the idea that Media institutions were partisan and acted on a political agenda to purposefully manipulate the population, observing that the reliance on social media, as the only source of information has been increasing.

However, social media lacks accuracy by exposing many users to conspiracy theories, clickbait, hyper partisan content, pseudo-science, and even fabricated “fake news” reports. This low-credibility content seems to spread quickly and easily and, because social media’s algorithms act in ways which reinforce pe7ople’s biases, it exposes the users to the type of content to which it previously engaged positively. Therefore, in recent years social media giants have been criticized, being forced to walk on a thin line between misinformation prevention and freedom of speech.

With its steady growth, QAnon changed from forums like 4chan, to social networks like Facebook, Twitter, and YouTube, increasing its access to millions of people. Between March and June 2020, during the COVID-19 pandemic, QAnon activity nearly tripled on Facebook and doubled on Instagram and Twitter, which also serve as a platform to radicalize milder conspiracy theorists, such as anti-vaxxers, into full QAnon believers later linked with far-right movements.

Some social media companies currently imposed tougher restrictions on their platforms. In 2019, Twitter removed several accounts that were supposedly connected to the Russian Internet Research Agency that had been disseminating a high level of QAnon content. Later, in July 2020, Twitter initiated an all-out ban on QAnon’s affiliated accounts and promised changes in the algorithm in order to mitigate the spread of related conspiracies. Facebook also announced measures that limit the presence of QAnon contentment across its platform.

The calm after the Storm

There is nothing unique about the narratives spread by QAnon, they share many of the typical conspiracy tropes prospered in a time of political and social instability, using COVID as a powerful tool to increase its reach. More worrisome is that unlike at any other historical time, conspiracy theories now enjoy near unlimited access to huge social media platforms, where information can be spread widely with no accountability. In these platforms, there is an increase in the promiscuity of some of these theories with political movements, which use each other and social media, to leverage their popularity. It remains yet to be understood if Social Media companies have the technical capacity to restrict these movements and have the moral authority to assess which movements deserve to be restricted.

BioNTech and Pfizer: Project “Lightspeed”

December 30, 2020February 9, 2021by Awareness NewsLeave a comment

Almost one year after the beginning of the Covid-19 outbreak in Europe, we finally start seeing some light at the end of the tunnel.

The first COVID-19 case in Europe was registered on the 24th of January and everything points out to the fact that the patient zero was a German citizen. Now, a new year is closer and it’s also a German company which is leading the race in the development of a vaccine that could bring the pandemic to an end. The company is BioNTech, a biotechnology firm based in Mainz.

After the SARS-CoV-2 genetic sequence being made public in the 12th January 2020, BioNTech initiated the project “Lightspeed”. As the name indicates, the goal was to develop an efficient vaccine in the fastest way possible. Furthermore, on the 17th of March the German company announced a collaboration with the American multinational pharmaceutical Pfizer. Ironically, this company, located on the other side of the Atlantic Ocean, based on New York, was also founded by two German cousins, Charles Pfizer and Charles Erhart.

On the 18th of November, the joint venture between BioNTech and Pfizer started collecting results. The phase 3 of the study regarding the vaccine elaborated by both firms was announced to meet all the primary efficacy endpoints and demonstrated a 95% efficacy against Covid-19. In the sequence of this promising developments, it was submitted an emergency application on the 30th of November to the European Medicines Agency (EMA) in order to get the approval so that the vaccine can be used in Europe. EMA reported that, if there was enough data, by 29th of December this assessment would be completed.

However, Pfizer and BioNTech are not alone in this race and they face the competition of the partnership between Oxford and AstraZeneca and of Moderna, which submitted its application to EMA on the 1st of December. Since the starting of the pandemic, the race for the vaccine, and the consequent normality, brought the attention of several politicians eager to claim their role in solving an epidemic. Therefore, one of the most sensitive issues on the development of the vaccine has been who was funding the BioNTech and Pfizer vaccine. The US vice-president Mike Pence attributed the success of this joint venture to the public-private partnership created by the US administration to accelerate drug development. However, influential media, such as Bloomberg, had noticed that the funding came through BioNTech, the German partner, who received 377 million euros from Angela Merkel’s government.

What makes BioNtech’s vaccine so unique?

For decades has the science community argued between the clear worthiness of investment and a supposed utopian illusion of messenger RNA, or mRNA. Alongside with Moderna, this joint venture is now starting to commercialize the first ever mRNA vaccine, something that scientifically had always made sense, but until last November, had never been granted any approval by the Food and Drug Administration (FDA).

But What Is mRNA? Unlike conventional vaccines, which consist of injecting dead or weakened forms of the virus so that the immune system learns to fight it and usually take years of research and analysis, RNA vaccines are focused on delivering the virus’ genetic code into our immune system, instead of the virus itself, in the hopes of triggering a response based on anti-bodies able to fight this pathogen. This process, besides having a much more optimal logistical basis, it also takes away part of the time constraint the world is facing today, with positive cases showing no sign of slowing down. However, one big variable is still being questioned at this point, which is for how long can this vaccine provide you immunity? Based on the research and estimates available at this point, it is still uncertain of how long will the vaccine provide the desired immunity. Most likely it will wane over time, but it is unknown the amount of immunity retained in order to guarantee protection.

How will the vaccines get to consumers?

Vaccines have started to roll out, but its distribution will take months. Mass vaccination is expected to start only in 2021, because despite being the fastest vaccine to be developed in human history, it still needs to be delivered to billions of people under strict storage requirements for precaution. Countries face a four-by-four challenge: a vaccine arriving at four times the pace and requiring delivery at four times the scale.

At this moment several countries have given emergency approval, with the UK being the first country vaccinating people outside trials on December the 8th for certain groups, including people who work in care homes and health care workers at high risk. Pfizer and BioNTech have also gained approval in the US, where more than a hundred thousand people have been vaccinated, including the Vice-President Mike Pence as well as other senior officials. In the EU, the joint venture was approved by the European Commission on December 21st.

BioNTech has started mass producing the vaccine in its facilities in Mainz, Germany, with a target of 100 million vaccines in 2020, however recent information suggests the company cut back the target to 50 million doses. Using Pfizer and BioNTech’s facilities across the US and Europe, including the manufacturing site in Marburg which BioNTech acquired a from Novartis this September, the joint venture believes it can produce 1.35bn doses by the end of next year, although Pfizer will be in charge of most of manufacturing and shipping.

The vaccine will be distributed from Pfizer’s centres in the US, Germany, and Belgium, from where the 300 million doses ordered by the EU will be shipped. It will then be transported in purposely built boxes, packed with dry ice and equipped with GPS tracking, capable of maintaining the vaccines at -75 degrees Celsius. The suitcase sized transport boxes are reusable and can keep up to 5,000 doses of the vaccine at the right temperature for 10 days. Once it arrives at vaccination centres, the vaccine can survive up to five days at temperatures between 2 and 8 degrees Celsius.

Transport box (source: BBC) — Transport box *(source: BBC)*

The nanoparticles present in the vaccine, which provide an increase in its effectiveness, are the cause of the strict temperature requirements. Other vaccines, as the one developed by the Oxford university and AstraZeneca, which resort to adenovirus rather than mRNA, do not require freezing, but approval is only projected for next year. The ease of transport and the consequent lower costs means this alternative could be used for mass vaccination in many developing countries, whereas Pfizer/BioNTech and Moderna’s vaccines will most likely be used for groups of risk who require a faster solution.

So, what does the future holds on for us? As the first vaccination phase takes its initial steps in the West, questions about a countdown to normal life has finally started. Supposing everything goes in accordance with expectations, US specialists predict May to be the month of “new normality” where the herd’s immunity threshold is reached but, of course, in a far-fetched scenario where all the Supply Chain’s structure is not mismanaged in that course of time. Until then, it is still fair to say that the use of masks and constant disinfection is going to be our greatest shield against the Covid-19 pandemic.

Sources: Financial Times, Bloomberg, MarketLine, McKinsey, Pfizer, New York Times, UK Government, Federal Drugs Administration, SIC Notícias, BBC, Sábado

Nudgers secret weapon: Randomized controlled trials

December 23, 2020March 3, 2021by Awareness NewsLeave a comment

Policy interventions that base themselves on behavioral economics findings have emerged heavily in different governments over the past 2 decades. The Behavioral Insight Team (UK) is one of the most recallable instances of nudge units that provided for research advancements and interventions of such kind. From using social norms to increase tax payments, increase fine payment rates, or using lotteries to increase election participation rates among voters, the approach that any result had in common was the extensive use of a statistical experimental method that changed science for good: randomised controlled trials. This article explores the methodology, why it is useful as well as its limitations, along with real life examples to provide an informed take on why is of essential importance within the behavioral economics field.

A Randomized control trial (RCT) is a type of scientific experiment that aims to reduce certain sources of bias when testing the effectiveness of new treatments. It consists in the randomized selection of two or more groups inside the population in study, where one group is the experimental one, which receives the intervention being assessed while the other, commonly called the control group, receives an alternative treatment in which there’s no intervention. The groups are monitored under equal conditions, in order to determine the effectiveness of the experimental trial when compared to the control group, since the only expected difference between the groups is the outcome variable in study.

Pro’s

RCTs are useful tools to answer medical-related experiments, being one of the most efficient ways to study the safety and effectiveness of new treatments, required by governmental regulatory bodies as the basis for approval decisions. This provides a very powerful response to questions of causality, as it allows the program implementers to assure the outcomes obtained are, in fact, a result of the variable in study, considering all other variables constant. As so, it eliminates any bias that may hinder the experiment, improving the veracity of the results achieved. RCTs are, in fact, the safest method for establishing cause–effect relationships, and they are often used to rigorously evaluate nudge interventions.

Con’s

Nevertheless, RCTs are not always the answer, and should only be used to evaluate nudge interventions whenever appropriate. The truth is, sometimes they are simply not feasible. Let’s consider the example of a school intervention: many times, the processes of randomization are not possible to perform in classrooms where all students are exposed to it. RCTs can also be considered unethical, in experiments where the intervention group clearly benefits with its application. For instance, if a school decides to expose only half of the students to an experiment that helps them build a CV, the other half will undoubtedly be harmed, due to the randomization inherent to the selection process. Additionally, RCTs may not be able to guarantee equivalence between the groups when dealing with a small sample, which may result in an unpowered test, unable to detect the real effect of the variable being studied. Lastly, if participants in different experimental conditions are in close proximity, as it might be the case in experiments among the population of a company, in which participants share their workplace, there may be communication between them, harming the veracity and credibility of the results.

The use of RCTs by Behavioral Economists

The application of psychology in public policy has been gaining tremendous importance in the past decade, as Governments have been realizing that their policies may depend on social, emotional, cognitive and many other factors usually disregarded by economists. Behavioral Economics is the science that embraces the psychological aspects of policies, and RCTs are the most important tool to which it resorts to. Leading to significant contributions to known cognitive and perceptual biases in our decision-making processes, the application of Behavioral Economics to public policy is occurring in diverse settings, from promoting a sustainable use of energy at home, to encouraging the timely and honest payment of taxes. These public policies have usually derived from centralized labs or innovation hubs specifically set up within government departments to rigorously trial and disseminate findings.

As introduced before, the most well-known example of RCT applied to BE is the United Kingdom’s Behavioral Insights Team (BIT). Having advised the UK’s Government since 2010, the BIT has been working across multiple domestic policy areas with the intent of improving public policy in general, by promoting the methodology “Test, Learn, Adapt”. The suggested approach was created with the purpose of dismantling the idea that RCTs are expensive and difficult to implement, by showing the Government its endless advantages in offering quick feedback to improve policy making. The BIT’s innumerous interventions over the past years have saved the UK government tens of millions of pounds, through the combination of a rigorous evaluation by the highly regarded psychologists, economists and policymakers who compose the team with new insights and approaches, with the use of RCTs as the most essential tool to test the effectiveness of these evidence-based policies. The BIT’s remarkable success has led many other countries to follow similar paths and create some type of Government-led initiative influenced by Behavioral Economics.

Allow us to consider a real-life example: in Canada, where behavioral economics is playing an increasingly important role in the development of its policies, with the establishment of many agencies rigorously testing their prospective behavioral interventions through the application of RCTs, it was made a behavioral intervention involving the promotion of organ donation registration rates in Ontario. The experiment was developed by the government agency Behavioral Insights Unit (BIU), which intervened with the purpose of simplifying the registration processes. The trial contributed to an increase of organ donation registration rates by 143%, due to the province of Ontario’s opt-out default policy framework. The RCT implemented by BIU allowed them to compare the effects of the different treatment periods to before and after the intervention, and to determine which treatment contributed the most to increase registration rates.

Although the incorporation of behavioral economics into public policy initiatives is not the solution to every political concern, it has proved to be a very important tool in this regard, as this intervention in Canada allowed us to conclude.

However, it is not only in the public sphere that RCTs are used. In fact, many private entities resort to this type of scientific experiment to prove the effectiveness of certain behavioral interventions.

Let’s consider a real-life example to better understand how a RCT can be helpful to the private sector: The Rector of the University of Virginia organized a RCT to find out the relevance of three different nudge interventions the university was considering to apply, with the goal of increasing college attendance and graduation rates. As so, the university selected three random groups of students, which received one of three messages: about the financial benefits of completing the Free Application for Federal Student Aid (FAFSA); reminding them or their motivation for applying to college; or with instructional guidance on how to complete the FAFSA. The study ended up finding out that none of the used nudge interventions had a statistically significant effect on students’ persistence into their second year of college, as the effects were close to none. It was concluded that this was a well-conducted RCT, since it provided valid findings and allowed the university to reject the application of the previously considered interventions.

In essence, it is safe to conclude that RCTs are one of the most valuable tools used by behavioral economists, not only as a powerful aid on policy making, but also on many private entities that desire to test hypothetical nudges before putting them into practice.

Madalena Andrade

Machine Learning (Part II)

December 11, 2020February 9, 2021by Awareness NewsLeave a comment

To all our readers, this is the second part of an article still brought to you by humans. We encourage all to go read Part I here in case you missed it.

Why all the buzz around machine learning now? Just how many of them are there? What are ‘Neural Networks’ (otherwise known as deep learning) and why do they threaten to take our jobs? And finally, how likely is it that my robot vacuum cleaner wrote this entire article? (Tip: More likely now than ever before)

Although similarities nowadays are sparse, Artificial Neural Networks got their name from being modelled after our own biological human neurons.

To broach a topic as diverse as Artificial Intelligence only raises more questions than it answers. This is especially true when writing an introductory article to the topic. As a result, the Tech team is dedicating a second story to further develop ideas brought to the table during the first part of our article.

From deciphering literally all questions that Machine Learning can answer – from an abstract perspective in the very least – to explaining some factors behind the notable rise of Neural Networks. In keeping in tone with the previous article, we’ll further explain some of the nuance behind Recommendation systems (such as the ones used by Amazon and Netflix) and the way these systems (traditional vs. new) complement each other.

The 5 most useful questions ever answered by Machines

When breaking down Tinder’s diverse processes, we saw how Learners could be utilized to perform several distinct tasks (image recognition vs. matching) and how one system built on top of another (new data powered other learners). The result of this systematic and iterative approach towards Machine Learning shows how data can be used to extrapolate powerful predictions. It is but one of many successful examples in how these powerful algorithms constantly shape our lives.

Our first part also provides a notion of the breadth and versatility of Learners. Much like how it’s said that all plots in media are variations of just seven basic story archetypes, it’s said that Machine Learning can only provide answers to 5 basic questions. When looking at a user’s Tinder profile in order to assign a trait or personality, we looked at what is called a Classification task – “Is this A or B.” Assigning a score to a user to predict a match with another user is what is called a Regression task – “How much or how many” – something not so (mathematically) different from trying to predict house prices. More towards the end of that story, we also brought up Clustering in regard to its potential uses in segmentation – in other words, “How is this organized”.

The two other questions, despite playing a very minor part, were also mentioned in some way or shape. They are: “Is this weird?”, useful in anomaly detection (also known as the reason why you shouldn’t use a credit card for one dollar purchases) and “What should I do now?”; a question that a machine is likely to ask itself whether being taught how to drive or when considering an insurrection against its human overlords.

Yes, there is a model called Logistic Regression . Yes, it is ironically cruel (especially if you’re hearing about all this for the first time). While objectively a Regression model (as in, it uses regression) it is used as a Classifier /for Classification tasks (e.g. based on the regression output, it will classify an object as A if below a 0.5 threshold or B if above 0.5) — Yes, there is a model called **Logistic Regression**. Yes, it is ironically cruel (especially if you’re hearing about all this for the first time). While objectively a Regression model (as in, it uses regression) it is used as a **Classifier**/for Classification tasks (e.g. based on the regression output, it will classify an object as A if below a 0.5 threshold or B if above 0.5)

While reducing all types of Machine Learning to 5 simpler questions might help you understand the nature of them, it likely puts you no closer to figuring out which one allows the GPT-3 model to produce human-like text. It might surprise the reader to learn that of all models in the diagram above, only one directly relates to Neural Networks – and that it does not explain the human-like text capabilities of GPT-3.

Much how Machine Learning is a field of techniques within Artificial Intelligence, Deep Learning is an entire field within ML. Many of them have been around for decades now – even before a time where computational power allowed for the efficient use of ML – often times in the form of scientific papers that could never go beyond conceptual form. Neural Networks, much like a lot of techniques in ML, grew in use and popularity as processing power turned many of these techniques viable.

In this sense, Neural Networks are the latest – and perhaps greatest – of ideas taken out of the Machine Learning icebox. From ‘Supervised’ to ‘Unsupervised’, the school of ML is capable of answering and solving any of these tasks. Going beyond versatility, it has also proven itself highly successful in performing tasks that traditional techniques, could not.

What Machine wrote my news?

Pretend for a moment that a Machine is capable of human-like thoughts (they aren’t, despite their increasingly impressive cognition). Would GPT-3, while outputting text, ask itself “How many?” or “Is this A or B?”

Furthermore, could a non-Neural Network learner have produced such an outcome? Can we say for certain that Neural Networks are inherently better than conventional techniques? For either question, it has to do with the quirks in data. Neural Networks, more specifically Convolutional Neural Networks (CNN), excel at the many challenges brought up with image recognition (namely high dimensionality). When faced with traditional techniques, Neural Networks will not perform inherently better outside of one notable exception – data size.

Past a certain (big) size, Neural Networks are practically guaranteed to be the better choice due to scalability. The bigger the data, the better it works when measured against other models. Work in Machine Learning has a lot to do with measuring and evaluating performance, and in keeping in tone, it has more to do with picking the better model than writing thousands of lines of code.

Additionally, often times we will find a mixture of both (Neural vs. Traditional) powering our increasingly complex systems. Consider Amazon and Netflix; both boast powerful Recommendation Systems, a million-dollar idea (Netflix Prize) that nudges you towards the next movie or item.

A traditional Recommendation System is a matter of matrix factorization. In simpler terms, it is one of the easier algorithms you can write by hand (and with just one or two courses of Calculus). Another thing is that Recommendation Systems pair you with something likely to be relevant – either due to similarities with other users or items – in essence, a Regression or Classification task.

At surface level, much remains the same by migrating to Neural Networks. Data goes in the model, and a prediction (whether regression or classification) comes out. The interesting part is how Recommendation Systems can be used to transform the data before it goes inside the model. Layered on top of each other, a learner can perform multiple tasks (answering more than one question) before reaching our desired output.

To return to our initial question, the secret to what GPT-3 might think before a prediction is likely to be “How much/How many” – it is described as an autoregressive model after all. But the secret to its success might be in answering multiple questions in succession.

Sources: Netflix Prize, The Ascent, The Awareness News, The Guardian, Towards Data Science.

Coulter, D., Gilley, S., Sharkey, K., 2019. Data Science for Beginners video 1: The 5 questions data science answers. 22 March

Pant, R., Singhal, A., Sinha, P., 2017. Use of Deep Learning in Modern Recommendation System: A Summary of Recent Works. 7 Dec

Machine Learning (Part I)

December 10, 2020February 9, 2021by Awareness NewsLeave a comment

“Machine Learning is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it…”

Machine Learning (ML) and Artificial Intelligence (AI) are buzzwords often used interchangeably in the casual and intellectual discourse of today. Many ideas often spring to mind when either is mentioned: data science, self-driving technology, big data and, on the more ridiculous side, robots hellbent on humanity’s destruction. The truth, however, is that Machine Learning is part of our increasingly data-driven world. It makes our lives better, despite several shortcomings, and is likely to be relevant to you even when not working directly with it.

Let us take a quick moment to make the distinction between ML and AI. Consider the picture above: Machine Learning, a subset of AI, is a field dedicated to generating predictions based on the hidden patterns, machines pick up within data. In practice, it is an AI technique where the machine writes its own rules. This means that a machine is fed with inputs (in tabular form) such as housing data or photos of dogs and cats, and it learns to perform a specific task without humans telling it how to do so.

In this article, we hope to explore some interesting case studies, such as how Tinder uses these learners to match you with your next date or how Amazon attempted to use an algorithm to analyse CVs (revealing a bias against women instead). With Tinder, for example, a machine takes our explicit (e.g. age range) and implicit (e.g. our photo was taken in a forest) preferences to match us with people likely to be a match. This is a task performed by several algorithms (or learners/machines), each one trained specifically for its task.

How does my swiping allow a Machine to learn?

Tinder uses an ELO-system, attributing a score to every user. Based on this score it will determine the likelihood of two individuals swiping right on each other, resulting in a match. This score is determined by multiple factors, such as the photos, bio and other settings of the profile, as well as swiping activity. Users with similar ELO scores, who have been identified as sharing similar interests, will be shown to each other.

Let us refer to the diagram below.

Firstly, the algorithm starts by analysing the user’s profile and collecting information from the photos they posted and personal information they wrote on their bio. In the photos, the algorithm can pick up on interests or cues such as liking dogs or nature. Through the bio, the machine will profile you based on words and expressions used (see picture below). From a technical perspective, these are distinct tasks likely to be performed by different learners – identifying words and sentiments is fundamentally different recognizing dogs in pictures.

At this point, Tinder does still not have much knowledge about one’s preferences and will therefore show your profile to other users at random. It will record the swiping activity and the characteristics of the persons swiping right or left. Additionally, it will identify more features or interests from the user and attempt to present the profile to others in a way that it will increase the likelihood of someone swiping right. As it collects more data, it becomes better at matching you.

The ‘Smart Photos’ option, a feature that places your ‘best’ or ‘most popular’ photo first, is also another instance where Tinder uses Machine Learning. Through a random process in which a profile and pictures are shown to different people in different orders, it will eventually create a ranking for your photos.

In Smart Photos, the main goal is for you to be matched. This works best when the most relevant picture is placed first. This could mean that the most ‘popular’ photo – the one that performed better – might not be the best; think of someone who likes animals. For these people, the photo of you holding a dog is likely to be shown first! Through the work of creating and ranking preferences and choices, a match can be found solely on the valuable insights from a photo.

By and large, the techniques that match you with other people as described above are part of a school of techniques in Machine Learning called ‘Supervised Learning’. In other words, the algorithm that learns to identify dogs and nature has been trained with similar pictures of dogs and nature. These stand in contrast with other schools, such as ‘Semi-supervised Learning’ and ‘Unsupervised Learning’.

The Perils of our (Human) Supervisors

In 2014, a group of Amazon engineers were tasked with developing a learner that could help the company filter the best candidates out of the thousands of applications. The algorithm would be given data with past applicants’ CVs, as well as the knowledge of whether said applicants were hired by their human evaluators – a supervised learning task. Considering the tens of thousands of CVs that Amazon receives, automating this process could save thousands of hours.

The resulting learner, however, had one major flaw: it was biased against women, a trait it picked up from the predominantly male decision-makers responsible for hiring. It started penalizing CVs where mentions of the female gender were present, as would be the case in a CV where “Women’s chess club” was written.

To make matters worse, when the engineers adjusted so that the learner would ignore explicit mentions to gender, it started picking up on the implicit references. It detected non-gendered words that were more likely to be used by women. These challenges, plus the negative press, would see the project be abandoned.

Problems such as these, arising from imperfect data, are linked to an increasingly important concept in Machine Learning called Data Auditing. If Amazon wanted to produce a Learner that was unbiased against women, a dataset with a balanced amount of female CV’s, as well as unbiased hiring decisions, would have to have been used.

The Unsupervised Techniques of Machine Learning

The focus up until now has been supervised ML types. But what of the other types are there?

In Unsupervised Learning, algorithms are given a degree of freedom that the Tinder and Amazon ones do not have: the unsupervised algorithms are only given the inputs, i.e. the dataset, and not the outputs (or a desired result). These divide themselves into two main techniques: Clustering and Dimensionality Reduction.

Remember when in kindergarten you had to identify different shades of red or green into their respective colour? Clustering works in a similar way: by exploring and analysing the features of each datapoint, the algorithm finds different subgroups to structure the data. The number of groups is a task that that can be made either by the person behind the algorithm or the machine itself. If left alone, it will start at a random number, and reiterate until it finds an optimal number of clusters (groups) to interpret the data accurately based on the variance.

There are many real-world applications for this technique. Think about marketing research for a second: when a large company wants to group its customers for marketing purposes, they start by segmentation; grouping customers into similar groups. Clustering is the perfect technique for such a task; not only is it more likely to do a better job than a human – detecting hidden patterns likely to go unnoticed by us – but also revealing new insights regarding their customers. Even fields as distinct as biology and astronomy have great use for this technique, making it a powerful tool!

Ultimately brief, Machine Learning is a vast and profound topic with many implications for us in real life. If you’re interested in learning more about this topic, be sure to check out the second part of this article!

Sources: Geeks for Geeks, Medium, Reuters, The App Solutions, Towards Data Science.

LVMH Acquisition of Tiffany & Co. “The Wolf in Cashmere Sports New Jewelry at Last”

December 4, 2020February 9, 2021by Awareness NewsLeave a comment

In November 2020, LVMH announced it reached an agreement to acquire the US Jeweler Tiffany & Co for a record breaking $16,2 B. Almost a year has passed and the deal has not been completed, the two companies have been back and forth on the negotiations, involving lawsuits in courts and the French government.

The companies behind the drama

LVMH Moët Hennessy Louis Vuitton SA, commonly known as LVMH, is a French multinational firm, based in Paris, France. The firm was created through a $4 billion merger, in 1987, of fashion house Louis Vuitton with Moët Hennessy. LVMH is the world’s leading luxury goods seller, controlling around 60 subsidiaries that each handle a small number of prestigious brands, 75 in total. The subsidiaries are often managed independently, under the umbrellas of six branches: Fashion Group, Wines and Spirits, Perfumes and Cosmetics, Watches and Jewelry, Selective Distribution, and Other Activities. The oldest of the LVMH brands is wine producer Château d’Yquem, which dates its origins back to 1593. The company also owns luxury retailers, including a majority stake in DFS Group Ltd., a group of duty-free stores, and Sephora. The company sought to expand and diversify in the late 1990s through several acquisitions.

Tiffany & Co., commonly known as Tiffany’s, is an American luxury jewelry and specialty retailer, based in New York City. Tiffany’s is known for its luxury goods, particularly its diamond and sterling silver jewelry, but their offering also includes china, crystal, stationery, fragrances, water bottles, watches, personal accessories, and leather goods. It markets itself as an intermediary of taste and style. Tiffany & Co. was founded in 1837 by the jeweler Charles Lewis Tiffany and became famous in the early 20th century under the artistic direction of his son Louis Comfort Tiffany. The company operates retail outlets in the Americas, Asia-Pacific, Japan, Europe and the United Arab Emirates. Tiffany’s operates 326 stores globally in countries such as the United States, Japan, and Canada, as well as Europe, the Latin America, and Pacific Asia regions.

Why Tiffany & Co.?

LVMH, the largest player in the luxury goods market, had been looking to grow its “hard luxury” segment for some time, seeing a perfect contender in Tiffany & Co., a leading brand in jewelry manufacturing, in a period of significant M&A activity. Despite the drama around the acquisition, the operation is still the largest ever luxury deal, giving the French group led by billionaire Bernard Arnault a greater presence in its smaller segment.

LVMH is already the market leader in the “soft luxury” market, composed of clothing, leather goods, bags, and accessories, with this segment representing almost 40% of total revenue. However, the group has a smaller presence in the jewelry market, the so-called “hard luxury”, the deal would double LVMH’s size in this segment from $4,72 B to over $9 B.

The deepening of the presence in the jewelry market will increase the group’s capacity to compete with other leading players such as Richemont, Chow Tai Fook Jewellery Group, Signet Jewellers, and Pandora, in one of the fastest-growing categories in the personal luxury goods sector.

Tiffany’s network of over 300 stores across the globe would complement LVMH’s Watches & Jewelry division of 75 stores. Furthermore, the American company has greater presence in the United States, a market LVMH looks to consolidate, and among Asian consumers. In fact, Mr. Arnault believes Tiffany & Co. “would fit perfectly within LVMH’s portfolio of brands”.

The luxury market has been growing consistently, having greatly accelerated in 2019 driven by a stronger growth of the US and Chinese markets, with the Chinese market representing the most rapidly growing proportion of the global luxury goods market, due to the expansion of an aspirational middle class. Nevertheless, the industry has seen difficulties in expanding in recent years because of changing consumer patterns, particularly among younger generations who tend to prefer experiences and services, such as travelling and dining, in comparison to luxury goods.

Also, because of the pandemic, global demand has shrunk, the luxury market is no exception as demand is expected to drop by 30% in 2020, with a recovery that could take years. Horizontal integration can be seen as a way to strengthen the brand ahead of the storm.

Despite LVMH’s growing collection of brands, regulators have not seen the deal as harmful for consumers, the European Competition Authority says there is no danger of monopolization or restriction of consumer choice. In fact, the acquisition will not alter the competitive structure of the market, because of the low market concentration. LVMH will still face competition from several other manufacturers of luxury goods, including Cartier, Van Cleef & Arpels, Richemont, among others.

Turbulent negotiations:

LVMH acquiring the American luxury jeweler for a colossal $16.2bn seemed like a “too good to be true” offer coming from the French billionaire, dubbed “the wolf in cashmere” – and it was so. The offer based on an EBITDA ratio of 17, over 50% greater than Tiffany’s 10-year average at the time, was not going to stand as the COVID-19 pandemic promised a possible 35% contraction in 2020 in the luxury market, predicted by Bain consultants, with Tiffany’s earnings closely trailing that downturn, according to the S&P Global.

When the deal was first struck, the $135 per share (37% premium at the time) supported the added value brought by Tiffany & Co, notwithstanding the closure of major markets, namely China. However, when the lockdown reached Europe, investors began to jitter, dropping Tiffany’s share price to around $114. With 35 years of experience in the luxury industry, Arnault knew that this was his opportunity to alter the deal’s terms, despite the air-tight prenup signed by both parties and the costs of backing out ($575M).

Negotiation turbulence climaxed in early September, when LVMH threatened to pull out of the deal, following a request from the French foreign minister, Jean-Yves Le Drian, to delay the deal. Tension between Paris and Washington arose, after US President, Donald Trump, imposed customs duties on certain French luxury goods, following the French’s adoption of digital services taxes. LVMH’s CFO, Jean-Jacques Guiony, stated they were prohibited from closing the deal, and uninterested in lengthening the lock-stop date, resulting in Tiffany’s share price dropping by 8.4%, to $111.67.

Nevertheless, Tiffany & Co was determined to follow through. It filed a lawsuit against LVMH claiming the conglomerate was merely attempting to strong-arm the jeweler into dropping the agreed merger price, consequently breaching the transaction agreement. LVMH hit back with a suit claiming Tiffany’s “catastrophic” performance following the pandemic indicated dismal prospects for the future. Ad interim, predictions on the deal resulted in stock price fluctuations for Tiffany & Co.

Final offer

Conflict between the giants ended with the French luxury group agreeing to pay a total of $15.8bn, at $131.5 per share – a haircut of $425M, less than 3%, of the original price. Moreover, Tiffany’s would have to pay shareholders a dividend of $0.58 per share. All lawsuits were settled. Though LMVH’s course of action seems extreme for such a modest price cut, ultimately it was able to bulk up on watches and jewelry, boosting its portfolio in the “hard luxury goods”.

Whether Bernard Arnault suffered from buyer’s remorse or went from the “wolf in cashmere” to the “lamb in lycra”, and despite the hiccups brought about by governmental intervention, legal conflict and pandemic-induced economic slowdown, this marks the largest deal ever in the luxury industry.

Sources: Financial Times, Marketline, Statista.

Somaliland: A New Hope

December 2, 2020February 9, 2021by Awareness NewsLeave a comment

The main purpose of development economics should be to give any country or community hope. Hope for a future they own and where they can grow. But no hope is seen nor given to anyone in Somalia, as the country has been a disaster since the day it gained independence in 1960. With the premise of bringing the major native ethnic group of the Somalis together, the British and Italian colonies were unified. Its government started as a failed democracy, followed by a brutal dictatorship under Siad Barre, resulting in wars and many genocides across the country. The dictatorship lasted two decades, until in 1991, the government was dismantled by rebel armed groups. Afterwards, no government successfully took control. Somalia has been in a civil war with different factions fighting for control, being the perfect hub for terrorist groups, warlords and pirates. An absolute anarchy. The years go by and there is still no hope for the Somalis.

But there is one exception – Somaliland, a region of Somalia that belonged to Britain in the north of the country. It has had relevant developments and it’s starting to have its first foreign diplomatic relations. It possesses its own currency and even its own passport. Its achievements have been considered remarkable. Even though it is not internationally recognized as a country separated from Somalia (yet), it’s developing the best it can to become one.

In this article we will focus on this small wannabe country and try to ascertain if it can indeed become a successful nation recognized by the rest of the world or if it is just another African state waiting for its decline. Is there still any hope for the Somali people?

Map of the faction division in Somalia, as of 2017

A short story of tragedy

Somaliland has always been the odd one out in this unification, being always marginalized by the rest of the country. In 1978, during Barre’s dictatorship, with the goal of unifying other Somali dominated territories, the national government started a war with Ethiopia, which it lost. This defeat destroyed the economy of the country, the lives of its citizens and the image of its government. Because of this, in the mid-1980s, rebellions started rising. Somalia’s military started a brutal counteroffensive, not only against the rebels, but also against the different clans that supported them. It was in Somaliland that the national army marched to the region’s largest cities of Hargeisa and Burao. Using artillery and air strikes, they bombarded the cities, destroying 90% of Hargeisa and 70% of Burao, killing thousands of civilians. This is known as the Isaaq Genocide. Barre’s government collapsed in January 1991, and in April of the same year, Somaliland declared independence. All Somaliland militias were dismantled or incorporated into the new national army of Somaliland, providing a solid stabilization and security in the region. For the rest of Somalia, a long civil war awaited.

On the road to a better future

For Somaliland to become a successful country, there are some key points that must be assured: regional stability, an efficient government and a healthy economy.

Somaliland is considered the most stable region in the Horn of Africa. As the former militias join the national army, this army remained loyal to the new government. After the remaining of Barre’s forces were defeated, many other dangers were still present, such as Islamic terrorist organizations, pirate groups and the other numerous factions in the civil war. All were successfully expelled. Its major stability problem is still with the neighboring Puntland with whom it has some territorial disputes. As of national identity, these were the same people marginalized by the rest of Somalia and the same clans killed in the Isaaq Genocide. We can associate the loyalty of Somaliland’s troops to this strong national identity.

Its government started as a democracy that distributed all major powers between the most powerful clans. Later in 2002, it decided to substitute it for a more ideology-based democracy. This new government had a modern constitution, with full separation of powers between independent institutions. In 2003, the first president of Somaliland was elected, and the subsequent elections have been all considered fair and legitimate internationally, largely thanks to this government architecture that was built with no help from abroad. All of this made Somaliland’s government gain the recognition of most efficient democracy in East Africa.

As for its economy, despite having great potential, it’s still quite underdeveloped as it continues to be based on livestock exports, largely to Arab countries. The government is progressively looking to diversify its economy, investing in its most promising sectors. Somalia is situated in the Horn of Africa, a valuable strategic location since it’s where many trade routes pass through. Somaliland took advantage of this by investing in its ports. Berbera’s Port is one of the biggest and most developed ports in the region and is a booming site for maritime operations, providing access for maritime trade and attracting foreign investment from China and the UAE. Its territory also has an abundance of mineral resources, such as industrial ore like iron and titanium and even rare metals. Oil reserves are also present and have already started being explored in 2018.

To summarize: it’s the only stable region in Somalia, as well as one of the most efficient governments build from the ground that has a promising economy. This great potential is not officially recognized in the world, but in many ways, it is unofficially: it has trading agreements with multiple countries, such as the UK and Taiwan, and is a member of multiple international organizations such as the UN’s Unrepresented Nations and Peoples Organization.

Somaliland representative Mohammed Omar Hagi Mohamoud meeting Taiwan’s President Tsai Ing-wen

Current problems

There are still many weaknesses inhibiting the self-declared country from being recognized. For instance, the ongoing civil war with the north-eastern area of Somalia – Puntland, due to the territorial dispute over eastern provinces, whose control is claimed by Somaliland based on colonial boundaries and by Puntland based on tribal affiliation. Another obstacle is that many countries and international organizations, including the African Union, don’t support a successful separatist’s movement, no matter how efficient it may be, fearing it may encourage other similar movements to seek independence. And because it has no recognition, no foreign aid can be provided to the government. Hence, the government is very dependent on private donors and investment, leaving the danger of corruption of the government wide open.

Apart from its lack of recognition, Somaliland also has many internal problems. It still presents an extremely low GDP per capita of $347 US, making it the fourth poorest country in the world, according to the World Bank. As the effects of climate change increase, it endangers the livestock industry, which is still the backbone of the current economy, resulting in income loss and famine to a part of the population. Despite Somaliland’s efforts and investments towards education, half of the children still have no access to school. Several human rights abuses are still committed, such as feminine genital mutilation, which unfortunately is still very popular in Somalia as it’s estimated that 98% of women have been submitted to it, according to ActionAid.

The Veredict

Truth is, this reality is very complicated. It takes a very long time to see improvements in a country, and failed cases of separation are the most common examples. But against all odds, this government has been achieving all the right benchmarks in the 30 years of its independence: stability in a region globally known for widespread chaos, a complex political system that disapproves and punishes corruption and a promising economy built with investments in infrastructure and education. Moreover, by granting international recognition, the resulting provision of foreign aid would alone solve many of Somaliland’s problems. But one question remains: if the international community doesn’t reward this nation, how can it expect to see more of its kind in the future?

Sources: World Bank, East African Business Week, UNICEF, UN News, The Conversation, Institute for Security Studies, Economist, Britannica, BBC, Action Aid, The Taiwan Times

The Rise of Far – Right in Portugal

November 27, 2020February 9, 2021by Awareness NewsLeave a comment

Portugal left wing history

The Third Portuguese Republic was implemented after the Carnation Revolution on April 25th, 1974. This movement overthrew the fascist regime that had been in power since 1933, established by António de Oliveira Salazar, the main figure of Estado Novo (“New State”).

The first democratic elections in 1975 were won by the Socialist Party (PS). Thereafter, the only parties with a majority in Parliament or with a respective prime minister were the socialists or the social-democrats (PSD). Other parties would only be part of the government through coalitions. Historically, Europe is categorized as moderate inclining towards social democracy.

In recent years, Europe, Portugal included, have witnessed a rise in radical right movements. Portugal’s main figure is Chega! (Enough!), a rightist, populist movement led by André Ventura. Although not the first party located further right of the Portuguese political spectrum, it was the first to gain notoriety and a seat in Parliament. The former National Renovating Party (PNR) is a self entitled far right party with very narrow public adherence.

André Ventura

André Ventura, born on January 15th, 1983, had a brief passage through the seminary (an attempt to follow priesthood), which fits some of his catholic conservative statements. Ventura ended up pursuing Law at Nova University of Lisbon, graduating with a 19/20 GPA. The PhD thesis he presented at Cork University criticized the stigmatisation of minorities and expressed his concerns on the expansion of repressive powers from the state.

In 2001, he joined the Social Democratic Party but only gained visibility in 2017 as a sports commentator on national television. This led to an invitation inside the party to run for the local elections of the Loures municipality. As a candidate, Ventura claimed that Roma people residing in Loures “live almost exclusively on public subsidies” and “think they are above the Rule of Law”. His declarations and hostile position over various social matters hindered the relationship with PSD leading to his disaffection from the party in 2018. In

April 2019 he founded Chega!. Representing it, André Ventura ran for the 2019 legislative elections (providing him a seat in Parliament), and is currently running for the 2021 presidential elections.

Chega!

“The Portuguese far right party” built its marketing as an anti-system movement – it claims the establishment is corrupt and does not have the people’s best interests in mind. The party seeks to establish a new and Fourth Republic by, among other measures, implementing a new constitution, as can be read in its manifesto (2019). The latter is intensely economically liberal and endorses a minimalist State on, for instance, education and healthcare services. Its political program includes fiscal reforms: the abolishment of double taxation on corporate income; reduction of VAT; and the adoption of a “flat income tax”.

On the other hand, Chega is strongly conservative on societal issues, which include motions such as the prohibition of gay marriage, of LGBTQ+ propaganda, abortion or any situation that “violates human integrity”. Furthermore, its program introduces chemical castration as a legal punishment for convicted pedophiles, among other severe penalties. Chega recently affiliated to ID (Identity and Democracy), a European parliamentary group composed of nationalists, far-right parties and eurosceptics, namely Alternative for Germany, National Rally (Marine Le Pen) and Lega Nord (Matteo Salvini). The group stands for national differentiation and administrative preservation of autonomy, alternatively to a European selfhood. Chega first presented a candidate for the european elections in 2019, leading a coalition named Basta!. It failed to elect a MEP.

The latest October 2020 legislative poll, conducted by Aximage, placed it with 5,4% of vote intentions. This consistent growth was confirmed by the regional elections in the Azores. The party gained 5% of votes, fourth most voted. Two regional MPs were elected and with no clear majority of votes in the elections, these two will be fundamental for the configuration of the new regional government. The party has gained recognition and consolidated its political force.

Electorate’s Profile

Studies conducted to identify the typical voter of a far-right party in Europe concluded he is a young poorly qualified male. Generally, he is a worker or a small businessman, if not unemployed.

In Portugal, the first study to provide an identification of this typical voter was a poll published last February by ICS/ISCTE. Given the European context, it came to contrasting conclusions. The typical radical right elector in Portugal has qualifications above the mean of the Portuguese population, mainly middle-class, namely office employees living in metropolitan areas. Furthermore, the electorate is evenly split between male and female. According to CESOP, the voters of the party previously voted for the two main parties or abstained.

Reasons for Widespread Growth

Populism is a political approach, which strives to appeal to ordinary people who feel their concerns are disregarded. The 2008 crisis and subsequent stagnation significantly worsened the middle class. Their substantial tax burden and the subsidies paid to those who “do not respect the Rule of Law” lure them to Chega, as proven in the ICS/ISCTE poll.

André Ventura often appropriates the popular contempt with a dividing logic of “us” against “them”. There is a large share of society which, after being constantly immersed in scandals and corruption at the highest levels of Public Administrations, feel as if “all politicians are the same”. André Ventura’s concept is appealing to the average Portuguese, who possess a sense of distrust towards politicians in general, thus embracing the anti-system propaganda. This could be why Chega has developed a hostile environment with most parties. This, paired with its image as a xenophobic and racist party, influences other parties to distance themselves, afraid of an electoral backlash.

Cultural liberalization and imigration are pointed out as troubles by Chega. In its manifesto, there are many references to an ideological proselytism: the attempt to change people’s beliefs. This concept is referent to LGBTQ+, BLM and other movements, which Chega frequently lessens, attracting social conservatives and clashing with leftists.Likewise, Chega seeks to strain the process of granting Portuguese citizenship, standing fiercely against the recent Nationality Law, eventually enacted. Illegal immigration is adressed by Ventura, although the Portuguese electorate cannot relate to that issue as well as larger European countries: contrarily to what happened to countries such as Germany, Greece or Italy, the Portuguese borders have only had some minor predicaments with refugees, never a worrying affair. Therefore, regarding intercultural matters, the main argument brought up by the party has been directed towards the Roma people and others living on subsidies. The leader of the party often accuses them of not complying with Portuguese laws, women’s and marriage rights, as well as respect for authority. During the pandemic, Ventura supported a special confinement for a Roma community outside a small city that refused to be subject to testing.

Nonetheless, the main explanation regarding the rampant rise of this party is the spotlight offered by the media in general, and the wideness of Ventura’s presence in social media. There have been weekly constant mentions and polemics around his name and party. Correspondingly, that has been the method chosen by European far-right parties which appears to be successful. Also, the fact that mainstream parties commonly criticize him helps the branding of the party as the solution for a damaged structure (given the “system” is against him, he should then be considered “anti-system”).

source: jornal “SOL” - “Portugal is not racist” movement against BLM movement — source: jornal “SOL” – “Portugal is not racist” movement against BLM movement

Conclusion

Portugal is not an exception anymore. In 2018, it belonged to a short list of countries in the EU without radical right representation in the Parliament. Today, it is another example of a substantial expansion of such a movement in a compact period of time. Nonetheless, it is important to say that Chega is not the typical far right party, for the latter (former PNR) has failed and lost vote intention to the earlier. The death penalty, a more extreme proposal, was presented and failled to gather internal support. Some claim the party is imploding due to an even more radical branch that starts to label Chega as another conventional party.

The Rise of Far – Right in Europe

November 25, 2020February 9, 2021by Awareness NewsLeave a comment

Extremist Movements in Europe

The origin of «left» and «right» terms concerning politics dates to the French Revolution, in 1789. One of the main topics debated when writing the new constitution was the amount of power the king would have. Among the present in the National Assembly, those in favor of the king having an absolute veto sat on the right side of the assembly’s president, while those who disagreed sat on the left side.

Nowadays, we use the terms left-wing and right-wing when referring to two broad opposite political points of view. The left is known for having a more socialist economic perspective, while the right commonly defends capitalism and a free-market economy. Throughout the years, both gave impetus to different extremist movements. When it comes to the far-right, although having different facets, this extreme side of the political spectrum is known for supporting nationalist, authoritarian and anti-immigration policies.

The Rise of Far-Right – Nationalism and Globalization

In modern politics, we tend to look at the far-right as a consistent political ideology, while throughout history it has been a quite flexible movement. Even so, there has been a prevalent feature: nationalism, particularly ethno-nationalism. Indeed, the core of the movement idealizes a version of a cultural, national, and historical identity, with the rhetoric that it is constantly under threat and therefore needs to be defended.

From the perspective of many right-extremists, globalization constitutes a significant threat to this feeling of «national identity». The free movement of goods, capital, services and people, the homogenization of culture, and the loss of economic independence are ways in which far-right movements have framed this holy war between external forces destroying the nation and the heroes defending it. Nationalism is seen by many as the savior that holds together the victims of tough and challenging times. Recently, for instance, Marine Le Pen, the candidate of the Rassemblement National in France, told supporters that globalization was «slowly choking communities to death». She backed up her statement with facts: globalization made many factories relocate from France to other parts of the world where labor was cheaper. This also happened in other European countries and heavily affected the middle class.

According to Arie Kacowicz, an academic expert on international relations, nationalism is one of the main resistors of media-induced globalization. However, there is a paradox: while nationalists often depict globalization, they also earn from it. In other words, changes in technology, for instance, create favorable conditions to the spread of right-extremist values. In fact, right-wings often use online platforms such as Facebook, YouTube, and WhatsApp so that their followers are constantly bombarded with breaking news and political propaganda. This enables them to connect with each other, creating a mechanism of echo chambers in which their own opinions and points of view are shown over and over.

The Rise of Far-Right – The 2008 Financial Crisis

Since World War II, the extreme-right has been seen with worrying eyes, but the 2008 financial crisis was the alarm buzz for the sleeping giant in the room. Recent years have witnessed an important rise of the far-right, taking over European countries’ political systems until today.

The crisis led to low economic growth, a rise in unemployment and an increase in inequality. It revealed an unexpected unregulated character of the market and main financial institutions, which in turn sparked mistrust of the ruling elites. People faced lower or stagnant incomes, as consequence of severe recession policies, and fewer job opportunities. Moreover, governments were not able to provide welfare redistribution, nor assist the transition to higher welfare. For instance, the British austerity measures ended up raising inequality, affecting the poorest the most, because, as shown by the Institute for Fiscal Studies, “the cuts have fallen in a disproportionate manner”

Indeed, the middle and lower classes were the most affected and found that help from the EU was scarce. As governments were decreasing spending and constrained on borrowing, some countries needed to resort to the International Monetary Fund (IMF), such as Portugal and Greece. Large economies such as Spain, France and Italy were also largely affected. Italy’s, Portugal’s, and Greece’s debt-to-GDP ratio rose and has remained above 100% of GDP until today. This happened, in part, because the European Central Bank (ECB) was unable to act as a lender of last resort, imposing austerity as one way to “save” European economies. Consequently, households felt hurt and blamed the EU for their newly found precarity. A Eurosceptic sentiment emerged among citizens and nationalistic ideologies were fostered through an increased support of far-right parties, which constituted alternatives to the governments who faced the crisis. Eminently, most European countries have seen a rise in votes for far-right parties in the last elections.

Debt-to-GDP ratio of Portugal, Greece and Italy

18 out of 28 countries in Europe saw a rise in votes for far-right parties comparing the last two elections.

Electorate’s Profile

According to the Horseshoe Theory, the political spectrum does not form a straight line but rather a horseshoe form. This means that the far right and far left, originally at opposite points of the political spectrum, would be closer and bending in toward each other. In fact, both left-wing and right-wing extremist parties target similar audiences.

Extreme-right voters are often young millennials or old nationalists who view the current far-right as broken and wish to restore it. Far-right politicians look for people who feel victims of the current government and angry with the state of things, people who feel subject to marginalization and ostracization.

Therefore, both extremist sides make use of populist speeches focusing on insecurities, fears, and emotions. They offer the audience a sense of stability, security and belonging, and provide simple explanations to reduce troubling complexities over complex questions, easily dismissing critical thinking. In their speeches, they create a sense of urgency of change, inciting radical action, sometimes violent, and occasionally leading to “sacrifices for the greater good”.

The Drivers of Right-Wing Extremism

Migration stands as one of the most important topics of European right-wing parties. In a recent poll conducted by the Italian News Portal, Affari Italiani, 65% of Italians said they feel threatened by migration and would feel safer under the more rigid policies of the previous Minister of the Interior, who blocked NGO-backed rescue boats from docking in the country. Additionally, terrorist attacks across Europe, including the recent beheading of a French teacher by a Muslim extremist in Nice, heated the anti-migrant sentiment in Europe. European citizens increasingly resent the EU and its handling of the refugee crisis, feeling that their well-being and safety are being threatened.

Arising from the consequences of the financial crisis, inequality and mistrust of the ruling elites also play a role. In Spain, according to the Pew Research Center, people are increasingly unhappy with the country’s political system and are lacking faith that the elected officials are up to the task. Inequality continues to be an issue since redistribution of wealth was not a priority on the agenda during the crisis.

Among European countries, there are several examples which demonstrate rising Euroscepticism. For instance, in the 2017 presidential elections, the French Rassemblement National led by Marine Le Pen, who opposed Emmanuel Macron and advocated for Frexit, reached the second round, only 2,7pp behind Macron. In Spain, the far-right Vox Party gained a lot of media coverage, since founded in 2013, becoming the third most voted party with 15,1% on the November 2019 General Spanish Elections. Finally, in Sweden, the Sweden Democrats are now on the top of the most recent polls.

Cartoon representing the battle for citizen’s vote between pro-Euro and anti-Euro parties in Europe.

There are, however, exceptions, like the Italian Movement Five Stars that is now getting closer to supporting the EU, even stating, in 2018, that the “European Union is the Movement’s home”. Another case is Poland’s current government which is considered softly Eurosceptic, believing Europe should help Poland and not the other way around, positioning against a federal Europe.

Conclusion

The right-wing is rising and came to stay. All over Europe, including Portugal, Spain and Scandinavia (countries where social democracy’s fall is not as strong as in the rest of Europe), the far-right is gaining ground against the left-wing parties. Anti-immigration and anti-Euro speeches are the used tool to convince voters. Inequality and discontentment towards democracy also constitute reasons for the people’s increasing support for the right-wing since the crisis.

However, recent polls point out to a decrease in the rise of right-extremist voting intentions. Almost all countries denote a fall regarding right-wing intention of vote, probably due to the current pandemic. People may prefer to vote for parties that can ensure more stability than more revolutionary ones when dealing with the CoVid-19 crisis. All this together raises a question: is the rise of the far-right decelerating or just starting?

Sources

Financial Times, Global Solutions Initiative, G1 Globo, The Guardian, Intereconomics, London School of Economics, New York Times, Pew Research, Politico, RMX, Time

Breaking the gender glass ceiling in South Korea

November 20, 2020February 9, 2021by Awareness NewsLeave a comment

In the 1960’s, South Korea’s fertility rate displayed an impressive and even slightly concerning population growth, leading the government to implement restrictive population policies. Nowadays, the scenario is significantly different, with the country’s fertility being one of the lowest worldwide. Combining that with an increasingly ageing population, South Korea is currently facing a decline in its population growth, with the natural replacement of generations being at stake. This concerning new demographic paradigm has led the government to take action, committing to increase the country’s birth rate, albeit unsuccessfully.

With these failed attempts, the solution may revolve around changing the women’s role in society, incentivising an active participation in the job market, granting them the same rights and benefits to those of men.

However, this raises the question: is South Korea’s society ready for such a drastic change?

Historical roots

South Korea was established as a nation with the division of the Korean Peninsula after World War II. In the aftermath, an invasion by North Korea of its southern counterpart´s borders triggered an armed conflict between the two, which was only solved by 1953 through the signing of an armistice agreement. Today, South Korea is one of East Asia’s most influential countries, with an economy ranking just behind Japan and China and a population of around 51 million people, of which more than 25 million are established in its capital, Seoul.

In recent years, South Korea has experienced a rapid industrial growth, as well as a vast economic modernization, contributing to the shrinking of the income gap that for many years separated it from the developed Occidental economies and, in some cases, to overcome some of them in GDP per capita (Graph 1). Nevertheless, even if in economic terms this gap is now practically non-existent, when it comes to gender equality and the women’s role in society, South Korea is still very far from the Western standards.

Graph 1 – Real GDP per capita comparison Source: Federal Reserve Economic Data — *Graph 1 – Real GDP per capita comparison*

*Source: Federal Reserve Economic Data*

Window-dressing gender action

With the ever-growing role of women in society after the late 1960s, as they increasingly sought and integrated the job market and pursued higher levels of education, the government enacted the Equal Employment Act in 1987, in order to guarantee equal and fair treatment across the two sexes. However, this proved to be ineffective in practice, as women continued to be victim of lower wages and sexual harassment in the workspace. As a matter of fact, South Korea is still today the worst-performing OECD country in terms of gender wage gap (median wage earnings of women are, on average, 32,5% lower than men’s, as shown by Graph 2).

Graph 2 - Gender wage gap across OECD countries (difference between median men’s and women’s wages) Source: OECD Data — *Graph 2 – Gender wage gap across OECD countries (difference between median men’s and women’s wages)*

*Source: OECD Data*

This discrimination in the labour market is still deeply rooted on the misconception that women are less desirable as employees, as they may require maternity leave in the future as well as leave to take care of their children, should they fall ill. Related to this is the patriarchal view that women are the ones responsible for the care of domestic affairs, leaving men to work to provide for the family. While efforts have been made in changing this current of thought (particularly, with the 2005 decision of South Korea’s Constitutional Court to abolish “hoju”, a family registry system that identified the head of household as a male and that obliged family members to be registered under him), it is still far from reaching the desired effects. In fact, the World Economic Forum and a United Nations report have recently ranked South Korea´s gender empowerment among the lowest in the developed world.

Therefore, this discrimination of women in the job market, centered around their role in the society, has forced many women to choose between professional success and family life, with many opting to forego entirely marriage and children. This is part of a rising social phenomenon in South Korea called the Sampo Generation, with the word ‘sampo’ meaning giving up three things: relationships, marriage and children.

A demographic winter

As a result of the Sampo phenomenon, birth and fertility rates plummeted in recent years, causing demographics in South Korea to take a concerning tumble. In fact, South Korea’s fertility rate has been declining steadily, not being able to reach the minimum threshold (2.1 children per woman, so as to ensure the replacement of the generation) for more than 30 years, nowadays reaching only 1.1 children per woman (an astounding contrast with the impressive rates registered in the 1960s, as seen in Graph 3).

Graph 3 - Total Fertility Rate in South Korea (1955-2020) Source: Worldometer — *Graph 3 – Total Fertility Rate in South Korea (1955-2020)*

*Source: Worldometer*

Moreover, longevity has also been improving in South Korea, with the country displaying one of the highest life expectancies in the world (around 82 years old), a value that the United Nations predict will continue to grow, estimating that, by the end of the century, an average baby born in South Korea will live to the age of 92.

This two effects combined result in an ageing population, with a population growth rate that has been significantly decreasing over the years (Graph 4), a fact that reinforces the notion that, even though a reduction in the country’s population is not yet a reality in the short-run, it seems to be an unavoidable scenario in the long run (Graph 5).

Graph 4 - Rate of population growth in South Korea (1960-2020) Data source: Populationof.net — *Graph 4 – Rate of population growth in South Korea (1960-2020)*

*Data source: Populationof.net*

Graph 5 - Estimated population of South Korea (2021-2050) Data source: Populationof.net — *Graph 5 – Estimated population of South Korea (2021-2050)*

*Data source: Populationof.net*

Promoting population rejuvenation

In order to combat this concerning demographic framework, various measures have been taken by the government in recent years, with a significant $70bn made available to be channelled into incentivising childbirth, marking it as one of the largest childbirth incentives worldwide, encompassing subsidies, facilities, as well as multiple perks for working parents and large families. For instance, in regards to subsidies, 500 000 won (around $500) are awarded to expectant parents so as to help covering prenatal expenses, as well as a monthly allowance of around 200 000 won ($200) during the infant’s 1st year.

Also, in recent years, the government has been working in providing free day-care services for everyone, implementing more flexible pick up and drop off hours,, as well as allowing for exceptions in which children of both working parents are attributed priority in long day-care waiting lists.

In addition to all these national measures, some specific cities, like Seoul, have applied localised measures such as subsidising fertility treatments, providing free parking or even offering housing assistance.

However, as of today, these measures appear to have had little impact in boosting birth rates. This is probably due to the fact that the issue of the problem lies not in monetary concerns, but on the deeply rooted mentality of South Korea’s society, which attributes primacy of work over family, making it hard for women to conciliate the two realities (inevitably leading them to choose one over the other).

Paving the way through the correction of a historical problem

The solution to this demographic problem seems to revolve around increasing women’s participation in the labour force, actively incentivising it by granting them the same salary rights as men, as well as offering more benefits for working mothers. In fact, this can only be achieved if women are allowed the proper balance between work and family, leaving them enough time to dedicate to their children, as well as granting them the maternity leave they are entitled to and also not using that matter as a discriminatory selection criterion in job interviews.

In sum, while this seems to be the best course of action to take in order to invert the current demographic situation, there is still a long path ahead when it comes to women empowerment in South Korea. In fact, even if some legal action has been taken towards the goal of gender equality, in practice, this change is yet to be felt.

Bridging the gender gap as the sole way of reinventing South Korea

As long as society’s mentality remains unchanged, it is unlikely that the government will succeed in combining an increase in women’s participation in the labour force with a rise in birth rates, dooming the country to suffer the consequences of a long economic and demographic winter.

Sources: Asiasociety.org, BBC, Bloomberg, History, JSTOR, Kostat, Populationof.net, The Economist, Wilson Center, World Bank, Worldometer