User:JREverest/sandbox/Approaches to Knowledge/2020-21/Seminar group 5/Evidence
Economical Evidence of Chinese influence on European affairsEdit
China has great ambitions for its future: Xi Jinping announced, during the 19th Communist Party Congress in October 2017, that China will be the new hegemonic global power by 2049. Examining economical evidence helps us notice that China is indeed present in European affairs.
From a purely quantitative evidential point of view, Chinese investments in Europe have been increasing for the past two decades and concern a variety of sectors such as infrastructure, airports, agricultural domains as well as soccer clubs. In 2016, these investments rose to 36 billion Euros. Most of these Chinese investments originated from private companies which only seek profit, meaning that it is harmless to the European Union and even contributes to boost markets inside the EU. Nevertheless, investments are also used by the People’s Republic of China, as Chinese companies are affiliated to the Chinese government, and allow them to buy political leverage.
The most famous example, Greece, illustrates this qualitative evidential proof. While the European Union was imposing austerity measures which Greece was struggling to follow, China massively invested into the country, gaining favourable diplomatic relations. Evidence indicates that one of the largest Chinese investment was the COSCO investment, which resulted in the purchase of 51% of the Piraeus Port Authority for 280,5 million in 2008. This project aimed to secure a transport corridor to connect directly China to Central Europe and followed China’s Belt and Road Initiative. Reducing the cost of transportation of goods and intensifying its presence in the EU market are indeed two principles which drive the “Workshop of the World”. This investment in Greece has helped China on a political level as Greece stopped unified statements from the EU condemning China’s human right record in June 2017. These actions have had effective consequences on the EU’s stance on an international scale, as such statements made at the UN gave the EU a position of a non-defender of Human Rights and Democratic Values. This example illustrates how closely related quantitative and qualitative evidence, as China uses its economic muscles (highlighted by the quantitative evidence) on European countries which has proven to help them on a political level, as evidenced by qualitative information.
In this context, evidence from a discipline-economics and politics-helps to draw our attention on pressing issues and support leaders’ decisions when it comes to imposing measures to restrain or punish other countries, other organisations.
The next interesting event would be European countries’ response to the growing Chinese presence on European soil. Based on the evidence it has collected, should the European Union block foreign influence? Or should it rather be less defensive and reinforce its own project based on openness and unity?
Evidence in economic decision modelsEdit
“What happens in the economy depends on what millions of people do, and how their decisions affect the behaviour of others. It would be impossible to understand the economy by describing every detail of how they act and interact. “(The Core Team, 2017, p.49). Models are used in economy “to see more by looking less”. Indeed, economic decision models help us better understand people’ economic attitudes and therefore, seem to lead to wiser decisions.
Nowadays, many organizations or institutions, such as trade unions or central banks, use economic models to make policies that will affect the lives of many. To have confidence in a model, organizations need “to see whether it is consistent with evidence”. “(The Core Team, 2017, p.51) After all, organizations don’t always make decisions based on rational principles. “Even a single organizational decision can be subject to heterogeneous interpretations depending on the model used in an analysis. » (Kuwashima,2014,p.1)
As written in International Trade Theory : The Evidence, “The intellectual power of the model lies in its simplicity, but this same simplicity causes great difficulties when one tries to translate the theory into predictions that might be worth exploring in real datasets.” ( Leamer, E. E., & Levinsohn, J., 1995, p.1344). That’s why, it is important to know when using an economic model, which factors are privileged and which ones are missing. Evidence in economic decision models is framed by a social aspect. A model as a simplified description of reality, is a subjective choice of priorities. What economics chose to measure or highlight in a certain model is a specific view of the world.
Moreover, “An inappropriate model structure may lead to unreliable model results “ (Cooper NJ,2007, p.1279 ) as a result the specific assumptions relating to model structure must be verified with different data. In order to verify a model, we need to compare model outputs with different data sources and different assumptions.
Evidence in Postcolonial StudiesEdit
Post-colonialism is the critical study of colonialism and imperialism, and explores the impact it has on today’s societies and structures.
In the UK, there are very few universities who offer Postcolonial Studies as a postgraduate degree, namely SOAS, Edinburgh, Leeds, and Kent of which SOAS is the only one to offer it outside of the English department. With post-colonialism, it’s essential to consider the perspective of the sources used. Their sources mainly consist of world literature, from African literature to Middle Eastern literature to New Zealand literature. Some of them use other forms of evidence to explore where colonialism can be seen to have an impact, such as film and politics.
However, it’s clear that some historical evidence of colonisation has been lost, forgotten, or rewritten over time. One example is how depictions of the Algerian war in French film and media have changed the narrative of the event. In subsequent French musicals and films following their failure at the Algerian War, there are references that allude to the war but never specifically mention Algeria; if it is mentioned, the characters representing Algeria are often portrayed as the aggressors. Therefore it’s important to recognise the limitations some sources have as evidence of colonialism.
Primary, anecdotal evidence is particularly used in post-colonialism. Ruth Skilbeck describes how the assimilation policies that were introduced when Australia became a federation in 1901 has caused significant psychological trauma in her family. In particular, she talks about the “Stolen Generations” of Australia - children who were taken from their families to be put up for adoption or raised as wards of the state. This was carried out from 1909-1969 so its impact is very current and will most likely still have an effect on generations to come.
The influence of colonialism has also been investigated in the economic sector, particularly as a factor of income inequality. Naturally, research on this has been through quantitative methods. Patricia Jones presents the idea that ex-colonies who had governors who were paid better have higher quality institutions today, which would explain why they perform better economically now.
Evidence in PhysicsEdit
Both qualitative and quantitative evidence can be employed when one considers disciplines within the Natural Sciences. Due to the scientific method and peer review, scientific theories are constantly being revised and revisited. This has been demonstrated through multiple developments within the Natural Sciences, and are usually facilitated by technological advancement.
When one considers evidence in Physics, there are a range of theories that have since been superseded due to the emergence of new evidence. Inna Vishik, a Doctor of Applied Physics & Physics, who received her Doctorate degree from Stanford University, describes science as "a framework for interpreting, systematising, and predicting nature based on empirical observations", rather than a subject founded in "absolute truths". This statement has been supported in the world of science severally. For example, before the Michelson-Morley experiment in 1887, many physicists believed that light waves required a medium in order to move across any given space. This medium was given the name "luminiferous ether". In 1820, physicist, Thomas Young conducted an experiment in which he was able to conclude that light is composed of waves, this led him to assume that just as sound waves require air as a medium to travel through, light waves require luminiferous ether. Young proposed that the existence of the luminiferous ether was "undeniably proved by the phenomena of electricity", although he was uncertain of the nature of their relation. In order to provide evidence for their relationship, Young carried out a series of experiments in which he calculated how much light would refract when a liquid was under electrical influence. Despite his efforts to generate quantitative evidence, Young's theory of luminiferous ether, amongst others, was later debunked by Edward Morley and Albert Michelson when they adopted his theory in an attempt to measure the velocity of the Earth. The results of their experiment disproved Young's theory, thus, leading all theories of luminiferous ether to be discarded of.
By conducting this experiment, Michelson and Morley were able to present new evidence suggesting the non-existence of luminiferous ether. This is merely one example which is suggestive of the evolutionary nature of physics, but more generally, the Natural Sciences, due to the acquisition of new evidence, and thus, new knowledge. It is important to recognise the flexible nature of evidence within the Natural Sciences, as it allows scholars within various scientific disciplines challenge evidence presented to them and respond with contrasting perspectives. Nevertheless, evidence provided may not always be conflicting, but rather, complementary, thus enhancing knowledge within the discipline.
Gathering Anthropological Evidence Through EthnographyEdit
Anthropological research emerged at the beginning of the 19th century, to a great extent out of the desire to study and collect evidence about unknown people in distant locations, during the period of European colonialism. Initially, this was done through ‘armchair anthropology’, which relied on (often racist and ethnocentric) secondary sources, such as exploration journals, written by travellers, traders and missionaries.
In the early 20th century, Bronislaw Malinowski established the qualitative research method of ethnographic fieldwork, specifically ‘participant observation’, as a significant method of gathering primary evidence within anthropology.
His work ‘Argonauts of the Western Pacific’ in 1922 became “the hallmark and quintessential model of fieldwork for almost half a century” due to his, at that time unusually long, fieldwork of 2 years in the Trobriand islands, as well as his active participation with the natives, achieved through learning the language (instead of relying on a translator) and taking detailed fieldnotes to document beliefs, behaviours, and social organization.
Following his example of collecting ethnographic evidence, later fieldworkers also developed relationships with the locals in order to encourage natural flowing and intimate communication in the form of informal interviews, and gain empirical knowledge though first-hand observation and experiential participation in the social activities of a community.
The norm for conducting ethnography is typically one year of fieldwork, although this is often determined by personal and budgetary constraints, which consequently impact the ability of anthropologists to learn the local language and fully immerse themselves in the culture they are studying. However, nowadays many anthropologists conduct their studies within their own society, thus avoiding such issues when gathering evidence.
Evidence in SociologyEdit
The discipline of sociology, being a social science, can produce evidence under many different forms. While some research resembles that of natural sciences, others would borrow researching styles used in humanities. Indeed, some evidence can be quantitative, coming under the form of numbers, statistics and tests. This kind of positivist methodology prones the idea of a 'right' and 'wrong' answer to a question or hypothesis. On the other hand, some social phenomena can't be quantified, which leads to the other type of research which is qualitative. This kind of evidence comes under the form of words, as it is the interpretation or formulation of concepts and thoughts. This kind of evidence includes interviews, reviews, field research or surveys for example.
Sociology being low-consensus discipline, sociologists don't all agree and follow one another on issues such as research and evidence. This has led to a historical divide between two major schools of thought: the Chicago school and the Columbia school. The first school of thought, birthed at the University of Chicago, is far more bent on qualitative research, and particularly, the use of case studies. However, this type of research should not be considered less scientific, on one hand because the Chicago School relies heavily on data analysis, and also because it was created specifically to counter the subjective 'arm-chair' sociology which dominated at the time. The Columbia School, which also came around during the first half of the 20th century, based its research a lot more on quantitative and empirical data such as statistics. It also focused much more on the biological and genetic causes of human behaviour, making it overall closer to natural science. This train of thought only lasted until 1927, but serves to illustrate the significant range of evidence and research methods among the social sciences.
However, if for better half of the 20th century, sociology used more qualitative evidence, recent years have seen the rise of science-based research. This is due to the fact that funding from government agencies is preferably given to 'evidence-based' research. The positivist vision, of a fact being either right of wrong, seems more appealing to most outside parties searching for reliability and validity in studies, which is why the theoretical side of sociology is sometimes undermined. One of the research methods which is largely used as a result of this is Randomized Controlled Trials, or RTCs, which are often used to test performance, and are therefore essential to a capitalist world. It is interesting to realise that financial resources and models affect evidence and research in academic fields.
Evidence in Documentary FilmmakingEdit
A documentary is a factual display of information derived based on situations experienced in real life. This is usually in film form. These tend to be a comprisal of a range of research methods; they tend to use mixed methods using a range of ethnographies, interviews and statistics. As well as this, ethnographers may present their findings in documentary form, and much research is made accessible to the public through this method. For example, Sally Denehy, Dr Alison MacDonald and Lasse Johannson published their documentary, funded by University College London, on PRU units and social exclusion in high schools on YouTube which made their findings accessible to anyone. Thus, documentaries are a way of presenting evidence. The kind of data and the methods used to collect it can be diverse and is largely determined by the discipline that is presenting it., though the validity of the information presented in documentary films are sometimes questioned.
Qualitative and Quantitative Data in DocumentariesEdit
Qualitative research is often used in documentaries as they are largely based on experience, as stated in the definition, and qualitative data focuses on rich information. Ethnography is a common way of collecting this, especially when presenting anthropological research as the aforementioned research did. Observation is commonly used in documentary filmmaking as one of the primary methods of collecting research, as people can be watched in order to understand evidence and the subject of their documentary. A famous example of documentary films that use observation is the Planet Earth series, narrated by David Attenborough, which observes animals in their natural habitats and attempts to explain and understand their behaviours from this evidence. Additionally, interviews are used in order to gain first hand qualitative data about knowledge and opinions, and to supplement the information gathered by observation in ethnography style research. Furthermore, documentaries will also use archival, literature and focus groups. Quantitative data is less commonly used, but documentaries use facts to back up and generalise their statements, applying their research from the group they studied to a bigger sample and highlighting its relevance. A lot of documentaries will use this statistical evidence at the beginning of their documentary in order to introduce their topic, such as Stacey Dooley's BBC3 documentary 'On the Psych Ward' which illustrates how qualitative data is used in the preface and introduction of documentaries.
Problems with Evidence Presented in DocumentariesEdit
There is sometimes doubt to the validity of the evidence presented in documentaries. There are websites and blogs dedicated to critiquing documentaries as they are generally assumed to be completely factual by viewers and this may not always be the case. According to William Rothman, the prevailing view in the 1970s was that regular entertainment films were just as fictional as documentary films, suggesting that there is a lack of valid evidence in documentaries. As briefly referred to, documentaries are taken as factual devices, suggesting that they contain completely objective truths. Despite this, they are subjective and are often subject to simplification, the documentary maker's own biases and film construction. They often encourage a view about something. This suggests that evidence used in documentary filmmaking is not completely valid nor reliable.
Evidence in ArchitectureEdit
The practice of architecture has been adapted in response to innovations across time. The architecture was during the 19th century influenced by engineering, and it was associated with chemistry and physics during the 20th century. Thus, the 21st century introduces architecture in the age of biology with a main biological evidence: the built environment affects humans mentally and physically.
In 1983, the scientist Roger S. Ulrich was the first to introduce the term EBD (evidence-based design) while studying the impact of a recovery environment on post-surgical patients. He observed that patients with natural-view through their window took fewer analgesic doses and recovered better than those with a brick-wall view. In 1993, the centre for Health Design was formed to improve the quality of healthcare facilities and defined EBD as an environment-design made on scientific evidence to obtain the best patient outcomes. EBD is today used for designing schools, office spaces, hotels, restaurants, museums, prisons, and even residences.
EBD originates from EBM (Evidence-based medicine) and works with a systemic approach through scientific rigour. It transforms with a methodological and qualitative approach, an intuition-based architectural practice into an evidence-based one. Dr. John Zeisel introduced EBD as a psychologic method-process applicable to general architectural research to understand how people respond to a design before the construction of the building.
In 1984, researchers Bill Hillier and Julienne Hanson from UCL created a tool based on rational thinking to analyse complex spatial relationships: the space syntax measures. Based on interactivity measures, space’s openness, and interaction spontaneity, it showed significant changes in offices with new patterns of behavior related to the layout of workspaces. The consistent scientific results found the hypothesis that in spaces, a general level of visibility makes staff interact more with each other and become more productive.
Evidence in StatisticsEdit
With the emergence of social media and our constant exposure to new information, statistics have gained an important role in filtering false and correct statements on the internet. In 2008, the University of California, San Diego, published a report showing that the average American consumes 33.80 Gigabytes of information per day. Hence, it is essential for information to be based on evidence. Statistics has sets of rules, rooted in a mathematical proof, to assess the truthfulness of the data, that we encounter constantly. Those rules, however, can be disregarded by individuals who in this process create false or misleading information. This issue is addressed in How to lie with statistics by Darrell Huff, published in 1954. Although the book was released over 65 years ago it discusses common misconceptions about statistics, that are even more relevant nowadays, with the increased amount of information we are encountering. One major finding he reveals is that correlation and causation are very different and not to be confused.
In research, qualitative and quantitative data make up the evidence base for the conclusions of the research and therefore need to qualify for such an important role. Statistics provide debated conventions to determine if the research can be used or not. These conventions concern statistical power and sampling size. The general requirement for research to be used is 80% statistical power, from which sampling sizes can be drawn. Some researches argue that there should not be one threshold that decides the validity of experiments, as this leads to an important amount of research being rejected due to lacking statistical power. Others defend that such a defined threshold is essential for research to be used safely. This debate shows how, even though statistics provide mathematical formulas to evaluate the likelihood of an experiment to be misleading, it does not offer an immediate response to whether findings can be used as evidence or not. Humans are the ones who decide this.
Evidence in Measuring UnhappinessEdit
The evidence-based practice is a scientific method of acquiring knowledge that requires experimental testing and expertise, as well as individual’s preferences. It is used to measure concepts throughout disciplines such as physics, medicine, education, economics and more.
According to the Oxford English Dictionary, happiness can be described as a non-long-lasting moment whereby someone feels pleasure and contentment. Happiness covers a wide range of interrelated concepts including among others well-being, hope, optimism, and life satisfaction. Its contrary, unhappiness, the sentiment of being sad or not being happy, can be measured through the lack of each of those concepts. Back in 1930, Bertrand Russell spotted eight drivers of unhappiness (meaningless, competition, boredom, fatigue, envy, guilt and shame, persecution mania and fear of public opinion) in The Conquest of Happiness, to which we could add illness, death of loved ones, poverty, and depression. Having said that, this paper is primary dedicated to approach evidence in unhappiness from an interdisciplinary perspective, as it is covering many notions from different disciplines including statistics, economics, psychology, sociology, and psychiatry.
Measuring Unhappiness through the lack of well-beingEdit
A concept is always broader than any of its proposed measures. Any suggested measure for any concept cannot fully capture the richness, the breadth and the depth of the concept itself. - Selim Jahan
The Oxford English Dictionary defines well-being as the “state of being or doing well in life; happy, healthy, or prosperous condition; moral or physical welfare (of a person or community)”. Well-being is qualitative and subjective. However, it can be measured quantitatively thanks to statistics and economics in order to evaluate a population’s happiness or unhappiness.
Measuring Unhappiness through well-being metrics and polling data - statistics toolsEdit
In Happiness for All? Unequal Hopes and Lives in Pursuit of the American Dream published in 2017, the author Carol Graham from the Brookings Institution and the University of Maryland writes about the different levels of happiness across rich and poor citizens in the United States of America. Based upon the Gallup World Poll and the Gallup Healthways surveys, the author mixes sociological, psychological and economic data available on people in order to explain unhappiness in the United States. With questions on people’s perception about their standard of living, such as “Please compare your life to the best possible life you can imagine on a ladder from 0 to 10” or “How satisfied do you think you will be with your life in 5 years?” as well as the use of demographic data (age, race, educational level…) and economic conditions, Carol Graham asserts that unhappiness can be explained among other drivers by the decrease of confidence related to social mobility, and the reduction of life satisfaction “by living in an area with hight income inequality”. Moreover, she says, as it is commonly agreed, that income plays a part in happiness and unhappiness and influences people’s beliefs, optimism, and hopes for the future and, it is less intuitive, that black Americans are more optimist than white Americans.
Measuring Unhappiness through the Human Development Index (HDI) - economicsEdit
Back in 1990, the Professor Amartya Kumar Sen and the Pakistani economist Mahbub ul Haq developed the Human Development Index (HDI), an economic indicator measuring human development through three components: health (long and healthy life), education (acquiring knowledge), and income (having access to resources needed for a decent standard of living). The purpose of this index was measuring and comparing well-being in different countries, as those economists believe that well-being go further than the level of an individual’s income. We measure HDI between the extremes 0 and 1. The closer a country’s HDI is to 1, the higher is its human development (and vice versa). These two examples show that unhappiness is not limited to the lack of income and, although this is a significant driver, psychological, sociological, clinical and ethnic drivers also play a significant role.
Measuring Unhappiness through a psychological, psychiatric and neuroscientific approach on depressionEdit
Depression is one of the many sources of unhappiness. It is a complex disorder, as even today, scientists don’t know for sure its drivers. As Huda Akil, a member of the Hope for Depression Research Foundation and professor of neurosciences and psychiatry at the University of Michigan, “A complex problem like depression is much larger than one scientist or lab can handle". On top of a neuroscientific and psychiatric approaches, Carrie Steckl proposes to include health and emotional conditions, but also social, spiritual, vocational, and environmental conditions in order to unravel the causes of depression. We guess that such interdisciplinary approach could also be useful when looking at other sources of unhappiness such as poverty and social downgrading.
Measuring unhappiness through a sociology perspectiveEdit
Suicide is a famous book written by the French sociologist Emile Durkheim in 1897 in which he claimed that capitalism is the driver of suicide’s increase and can explain the level of unhappiness. Indeed, he asserted that at his time, even if it is still relevant today as capitalism is ubiquitous and widespread over the world, capitalism made people become richer but also raised the pressure on the individuals. Indeed, he explained that the rise of individualism, rather than collectivism in traditional societies, have increased the sentiment of failure as people started to make their own choices without asking permission to their families and class they were born into. Consequently, it was their luck or their fault, if they succeed or failed. Durkheim estimated that there was an excessive hope, as people saw in capitalism the opportunity to become rich and independent, but not the possibility to be disappointed. As people started to make their own choices, capitalism emphasized freedom and removed some duty of behavior related to family and living in a community. Hence, people didn’t share a lot in common anymore and lost interest in one another activities and plans. The importance of religion in our life, with on the opposite the rise of atheism, as well as family values, have both weakened and triggered a decline in the sentiment of belonging that they used to offer. Therefore, sociological aspects are deeply rooted to unhappiness, as Durkheim asserted.
Unhappiness is a complex notion that has multiple drivers. Therefore, evidence in unhappiness can benefit from an interdisciplinary approach, as disciplines don’t measure unhappiness through the same variable. There is not only one way to estimate unhappiness: some disciplines use quantitative evidence, as we saw in statistics and economics, and others prefer qualitative evidence, as we saw in psychology and sociology.
Evidence in MathsEdit
The Start of Evidence in MathsEdit
Maths as a discipline is first and foremost, the base to almost every disciplines evidence, as it provides a quantitative base to any conclusion. Evidence in maths, is usually seen as 'proof', which is expected to be a stronger claim in the mathematical category of evidence, as the Greek mathematicians used the term evidence only associated with mathematics when it has been proven through many evidential systems.
Maths has its origin of evidence way back in 3000 B.C. when the ancient Sumerians developed the first written evidence of maths based on the system of metrology which was created in the early beginnings of their civilisation. The explosion and its split into different evidential parts of maths, began in Mesopotamia, as the evidence of the Sumerians was taken accountable and developed into arithmetic, geometry and algebra which find there evidence in the sexagesimal number system. Maths was always seen as a high class of evidence, as the systems of arithmetic, geometry and algebra, weren't only contributed by its origin, however, China, Egypt and Central America were proving the evidence of maths as we know it today.
However, until modern times, the evidence in maths took different paths, as 7 major schools divided their thoughts about mathematical evidence and approaches. Most of the mathematicians were finding their evidence to their concepts in theorems while others were trying to construct their evidence for their own good. The division although ended soon, as the Pythagorean School took the lead and was contributing to the start of calculus, where more evidence was found towards the field of calculus and the evidence for constructive and proven evidence became clearer. Calculus finally added the evidence to the field of mathematics, that there are two types of mathematicians, pure mathematicians who prove, and therefore show the theorems in the real world and applied mathematicians who construct theories. Calculus shows the evidence that both types are needed to reach the best possible outcome.
Evidence in form of TheoremsEdit
The first mathematical theorem which consisted of the same evidence until today, started with the idea of the Thales Theorem which was evidential discovered by Thales of Miletus. The basis to the evidence in maths began with Greek philosophers such as, Miletus and Pythagoras who was another Greek mathematician and philosopher, who discovered the Pythagoras theorem as the second theorem in maths with evidence behind it theory, which is still valid and applicable today. A famous example where maths and especially the evidence in maths through the use of the Pythagoras is applicable is the discipline of architecture to measure the height of buildings and the length of walls, as this was firstly discovered in ancient Egypt to build pyramids. These two theorems together worked on solution, therefore, evidence on how many types of mathematic evidence have to come together to create and prove the bedrock of any disciplines assumptions throughout mathematic proven evidence.
Evidence in CryptozoologyEdit
The term Cryptozoology is derived from the Greek words “Kryptos” (Kρυπτος), “Zoon” (Zον) and “Logòs” (Λόγος), meaning “the study of hidden animals”. The field was promoted as a subdiscipline of Zoology by the International Society of Cryptozoology (ISC), but the lack of empirical evidence to confirm the existence of such animals has limited it to its classification as a pseudoscience by the academic community.
Nevertheless, cryptozoologists carry out research based on indirect knowledge. As soon as there is information on a presumed unidentified animal, researchers examine the supposed geographical location of the animal through multiple aspects: its history, archaeology, folklore and mythology. If there was a sighting, cryptozoologists apply the methodology of Forensic Science: witness statements and circumstantial evidence (footprints, hair tufts, pictures, recordings, etc) will be collected, analysed and screened to provide a zoological explanation.
Cryptozoology is widely criticised for its reliance on eyewitness accounts as their primary source of evidence, arguing that it is inherently unreliable and thus does not constitute as valid data. Despite this, local knowledge has proven to be instrumental in the discovery of “new” animal species. For instance, Zoologist Marc von Roosmalen was told about sightings of differently coloured monkeys by locals of the Amazon, which led to the eventual discovery of five New World Monkey species, Callibella humilis, Callithrix manicorensis, Callithrix acariensis, Callicebus bernhardi, and Callicebus stephennashi.
Additionally, critics attack cryptozoologists for taking literal interpretations of local mythology and folklore. Researchers defend their methods explaining that real, rare animals are often distorted to become mythological creatures through a history of textual and oral tradition. Furthermore, they assert that zoological discovery would progress much quicker if they applied the interdisciplinary approach of cryptozoologists, instead of rejecting circumstantial evidence to fit the traditional scientific method. In 9th century Chinese and Japanese folklore, the mo (貘) or Baku was an a “mythological chimera with trunk of an elephant, eyes of a rhinoceros, the tail of a cow, and feet like a tiger” that was only de-mythicised to be the Malayan tapir (Tapirus indicus) much later in the 19th century.
- ↑ Phillips T. The Guardian. Xi-Jinping heralds “New Era” of Chinese power at Communist party congress (UK Edition.) [Internet]. 2017 October 18 [cited 2020 October 23]  Available from: https://www.theguardian.com/world/2017/oct/18/xi-jinping-speech-new-era-chinese-power-party-congress
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- ↑ Yu J. China’s geo-economic strategic: firms with Chinese characteristics: the role of companies in Chinese foreign policy [Internet]. London (England): The London School of Economics and Political Science; 2012 June [cited 2020 October 23]. 32-37. No.:1. Available from: http://eprints.lse.ac.uk/44205/1/__Libfile_repository_Content_LSE%20IDEAS_Special%20Reports_SR012%20China%27s%20Geoeconomic%20Strategy_China%27s%20Geoeconomic%20Strategy%20_Firms%20with%20Chinese%20Characteristics%20(LSE%20RO).pdf
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- ↑ John H, Scott M, Gailyn P. Journal of Infrastructure, Policy and Development [Internet]. EnPress Publisher; 2019 Chapter 1: Examining the debt implications of the Belt and Road Initiative from a policy perspective [cited 2020 October 23]. 139-141. Available from: https://systems.enpress-publisher.com/index.php/jipd/article/view/1123
- ↑ Helena Smith. Greece blocks EU's criticism at UN of China's human rights record (UK Edition.) [Internet]. June 2017 [cited 2020 October 23]  Available from: https://www.theguardian.com/world/2017/jun/18/greece-eu-criticism-un-china-human-rights-record
- ↑ The Core Team,2017. The Economy.’ Unit 2 : Technology, population, and growth’, 2,p.43-85. Available from : https://core-econ.org/the-economy/book/text/02.html ( accessed 7 November 2020)
- ↑ Leamer, E. E., & Levinsohn, J. (1995). International trade theory: the evidence. Handbook of international economics, 3, 1339-1394.
- ↑ Gürkaynak, R. S., Sack, B., & Swanson, E. (2005). The sensitivity of long-term interest rates to economic news: Evidence and implications for macroeconomic models. American economic review, 95(1), 425-436.
- ↑ Cooper NJ, Sutton AJ, Ades AE, Paisley S, Jones DR; Working Group on the Use of Evidence in Economic Decision Models. Use of evidence in economic decision models: practical issues and methodological challenges. Health Econ. 2007 Dec;16(12):1277-86. doi: 10.1002/hec.1297. PMID: 18034447.
- ↑ Kim, L. G., & Thompson, S. G. (2010). Uncertainty and validation of health economic decision models. Health economics, 19(1), 43-55
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