TOK Friends

In the study of TOK in DP-1 (11th grade), I have learnt about the ways of knowing, and two of the areas of knowledge - natural sciences and human sciences. Of all the discussions and explorations done into these areas of knowledge, there can be patterns observed in the methods of experimentation, data collection, data analysis and also assumptions being made when generalizing situations. In some of the above points, human sciences is similar to natural sciences, while in the others, the ideologies and working is different.

Natural sciences and human sciences for instance both use experiments as a form of data collection but the methods and outputs are different. Natural scientists have lesser moral values to take care of compared to human scientists such as psychologists. Psychologists are directly dealing with humans and hence need to take more ethical implications into consideration. Secondly, human scientists conduct experiments on a large set of people - not limited to one race or gender unless it is required. Natural scientists do not require survey type data. Here, a single scientist conducts the experiments. Both the types of experiments are empirical based though, direct experimentation is more in natural sciences while human sciences are more observation based. But experiments in human sciences have more unpredictable results due to what is known as the Hawthorne effect. This effect explains that when a particular group comes to know that they are under observation for a experiment or an analysis, they tend to be more productive. These cause errors in results of human science experiments especially the ones of psychology.

Should economics study the psychological basis of agents’ choice behaviour? I show how this question is multifaceted and profoundly ambiguous. There is no sharp distinction between ‘mentalist’ answers to this question and rival ‘behavioural’ answers. What's more, clarifying this point raises problems for mentalists of the ‘functionalist’ variety [Dietrich, F., & List, C. (2016). Mentalism versus behaviourism in economics: A philosophy-of-science perspective. Economics and Philosophy, 32(2), 249–281. https://doi.org/10.1017/S0266267115000462]. Firstly, functionalist hypotheses collapse into hypotheses about input–output dispositions, I show, unless one places some unwelcome restrictions on what counts as a cognitive variable. Secondly, functionalist hypotheses make some risky commitments about the plasticity of agents’ choice dispositions.

This controversy over the proper role of psychological concepts, explanations and evidence in economics is multifaceted and profoundly indeterminate, this paper will argue. In what way multifaceted? One facet of this controversy is the issue of whether economics should study the anatomical structures in the brain that underlie decision-making (Section 3). A second facet is the issue of whether economics should study the causes and effects of cognitive variables (Section 4). A third facet, I suggest, is the issue of whether economics should study the plasticity of agents’ choice dispositions (Section 6).

conomic models often give people credit for being what may seem at a glance an unexceptional thing: fully rational beings pursuing our own self-interest. But as psychologists, such as 2002 Nobel laureate Daniel Kahneman, and behavioral economists, such as 2017 laureate Richard H. Thaler, have pointed out, an assortment of biases, heuristics, and other factors often move us to behave in ways that seem distinctly irrational. Can social science’s understanding of how humans think and act be used to predict how markets will behave?

Although the responses tended to affirm the predictive power of behavioral economics, members of both panels reiterated that fully rational models still have an important place in economics. Pol Antras of Harvard, who agreed with the statement, added, “Still, models with fully rational agents provide a perfectly good approximation for explaining many market outcomes!”

"Psychology and economics are both interested in how people make decisions, but have different theories and methods. In our work with economists at Northwestern, Michigan, the Federal Reserve and elsewhere, we have found ways to complement each other's expertise," said Wändi Bruine de Bruin, professor of behavioral decision making at Leeds' University Business School, who received her Ph.D. from Carnegie Mellon University, where she is collaborating professor in the Department of Engineering and Public Policy.

Leading economics scholars consider the influence of psychology on economics, discussing topics including pro-social behavior, conditional trust, neuroeconomics, procedural utility, and happiness research.

Summary Leading economics scholars consider the influence of psychology on economics, discussing topics including pro-social behavior, conditional trust, neuroeconomics, procedural utility, and happiness research. The integration of economics and psychology has created a vibrant and fruitful emerging field of study. The essays in Economics and Psychology take a broad view of the interface between these two disciplines, going beyond the usual focus on "behavioral economics." As documented in this volume, the influence of psychology on economics has been responsible for a view of human behavior that calls into question the assumption of complete rationality (and raises the possibility of altruistic acts), the acceptance of experiments as a valid method of economic research, and the idea that utility or well-being can be measured.

Judging from mass media treatment of economic affairs — be it in a recession, in a more serious depression or in an upswing period — there should be ample room for psychology when economic issues are dealt with. Economists who appear in the public eye as authors of articles or as interviewees often stress the importance of psychological factors

Psychology is a science which explains behavior of people and it cannot be ignored that psychology has a profound effect on economics.

The overarching goal of science is to deepen our understanding about the world we live in, and then to use this understanding, for example, to address social or medical problems. However, in order to pursue those goals effectively and efficiently, the scientific findings we base our actions on have to be credible. But how can we assess the credibility of research? Is a going through peer review enough, or being published? What if the study made it into in a “high-ranking” journal? Is that enough to deem findings credible?

Curate Science is committed to rewarding positive scientific behaviors, but does not punish questionable research practices or lower levels of transparency. Researchers are encouraged to adopt open and transparent practices, but to do so  at their own pace. LeBel explains, “we make it easy to get the most credit possible for conducting and reporting one's research only a little bit more transparently. That is, as transparent as you currently have time for and/or are comfortable with. For example, if you're uncomfortable publicly posting your data for an article, you could still earn credit by publicly posting your code and linking to it on Curate Science” (Only 1 transparency component is required for being added to the database).

Science relies on empirical evidence and testable explanations. By basing its conclusions on multiple lines of evidence drawn from experiments and observations, science seeks to build reliable knowledge and provide scientific explanations that people can use to better understand the world around them and inform their decision making.

Right. Scientific research is both an individual and a collective activity. Scientists may act on their own in gathering data and working out ideas. But they then need to convey to others their conclusions and the methods and evidence on which those conclusions are based. These observations and conclusions can be checked and extended by other scientists.

What is not Common Knowledge? Datasets generated by you or others. Statistics obtained from sources such as the US Census Bureau and the Bureau of Labor Statistics. References to studies done by others. Reference to specific dates, numbers, or facts the reader would not know unless s/he had done the research.

If you are familiar with the notion of “common knowledge” from earlier writing experiences, you may have noticed that its definition is easy to state, but can be hard to apply in a particular case. The “common” way to talk about common knowledge is to say that it is knowledge that most educated people know or can find out easily in an encyclopedia or dictionary. Thus, you might not know the date of the most recent meeting of the Federal Reserve, but you can find it out quite easily. Further, the term “common knowledge” carries the sense of “communal” knowledge—it is community information that no particular individual can fairly claim to own. One sign that something is community knowledge is that it is stated in 5 or more sources. So, if it’s known to educated people, or can be easily looked up, or appears in many sources, it is likely to be “common knowledge” and so does not need to be cited.

Because the notion of “common knowledge” is ambiguous and depends on context, you should always check with a professor or TF if you have any doubts. Some reference books will say “if in doubt, cite it,” but you don’t want to over-cite, so check with your readers to try to fix the line between common and specialized knowledge.

This advice about “common knowledge” is true for all disciplines—think about your audience and the course attitude, recognize when you’re writing as an expert, and always check with professors if you’re in doubt. The sciences, however, have a somewhat different notion of “common knowledge,” coming partly out of research practice and partly out of more collaborative work methods. Ideas, findings, and methodologies that are new knowledge (and therefore specialized rather than common knowledge) become old knowledge more quickly in the sciences. The answer, again, is to consider the messages you’re getting from the course about what concepts are common or foundational, and to check in with professors or TFs.

haped abstractions called vectors. Pondering Hilbert space makes me feel like a lump of dumb, decrepit flesh trapped in a squalid, 3-D prison. Far from exploring Hilbert space, I can’t even find a window through which to peer into it. I envision it as an immaterial paradise where luminescent cognoscenti glide to and fro, telepathically swapping witticisms about adjoint operators.

Reality, great sages have assured us, is essentially mathematical. Plato held that we and other things of this world are mere shadows of the sublime geometric forms that constitute reality. Galileo declared that “the great book of nature is written in mathematics.” We’re part of nature, aren’t we? So why does mathematics, once we get past natural numbers and basic arithmetic, feel so alien to most of us?

Physicists’ theories work. They predict the arc of planets and the flutter of electrons, and they have spawned smartphones, H-bombs and—well, what more do we need? But scientists, and especially physicists, aren’t just seeking practical advances. They’re after Truth. They want to believe that their theories are correct—exclusively correct—representations of nature. Physicists share this craving with religious folk, who need to believe that their path to salvation is the One True Path.

Common knowledge is that which I know and that which I know everyone else knows. That, at least, is the easiest way to put it for my purposes here, which is how a large number of people came to believe that Donald Trump won the 2020 election—and subsequently constructed an intellectual edifice around this conviction that led to the January 6 Capitol riots.

David Lewis gave the most well-known account of common knowledge in 1969:Let us say that it is common knowledge in a population P that X if and only if some state of affairs A holds such that:1. Everyone in P has reason to believe that A holds. 2. A indicates to everyone in P that everyone in P has reason to believe that A holds. 3. A indicates to everyone in P that X.David Lewis, Convention (1969)In other words, in an imagined group of people P, you get common knowledge of “Trump won the election” only if you have a situation in which every member of the group is not only given reason to believe that Trump won the election, but also that everyone else in the group has reason to believe (and likely the same reason to believe) that Trump won the election.

One Year Together, Apart

The pandemic redefined relationships and self-reliance.

In the year since the pandemic began, people learned to be together while apart and navigated the pain of feeling apart while together

Unfortunately, though there are epidemiological experts and economic experts, and psychological experts and sociological experts, there are no scientists whose expertise encompasses epidemiology, economics, psychology, and sociology. 

It is, moreover, true that scientific consensus is often fleeting and regularly overturned, and that, in any case, consensus is neither unanimity nor a marker of infallibility. But the problem that we raise would remain a problem even if scientists were unanimous and infallible in their respective fields, and omnipotent about particular circumstances of time and place. 

Scientists learn their trades through specialized study of specific phenomena, which they investigate in isolation under carefully controlled conditions, holding other factors constant. The best scientists in their fields are experts about a very limited range of phenomena that are assumed not to interact or integrate with any other kinds of phenomena. Outside of the graduate seminar and theoretical model, be

Why ask “Why trust science?” When many people worry about the safety of genetically modified food, parents resist the advice of pediatricians to vaccinate their children against common childhood diseases, religious people still say they take the earth to be fewer than 10,000 years old, and the president of the United States declares climate change to be a hoax perpetrated by the Chinese, public trust in scientific research would seem to be in dire straits. The time is ripe for reassurance. Even to pose the question indicates that something has gone wrong.

We need to know why to trust science, then, in part because we need to know why to believe the scientific consensus on climate change, and Naomi Oreskes is the obvious person to provide the answer. Her new book takes up the question explicitly; it grows out of her Tanner Lectures on Human Values, delivered at Princeton in late 2016, and includes commentaries by a historian, a philosopher, and three social scientists.

But it is not just conservatives who question scientific authority in the United States. Alarm at many applications of biological research, for example, crosses party lines. This impulse usually targets genetic engineering and biotechnology, but it also fosters skepticism toward vaccination and other medical practices. Across the political spectrum, citizens tend to pick and choose among scientific theories and applications based on preexisting commitments. They are frequently suspicious of basic research procedures as well; many believe that peer review and other internal policing mechanisms fail to remove powerful biases. Conservatives often charge that peer review enforces liberal groupthink, while some progressives say it leaves conventional social norms unexamined.

Even as individuals, scientists face growing skepticism. Concern about scientific misconduct is widespread, and most Americans doubt that the perpetrators face serious repercussions. Significant numbers trust the experts who apply knowledge more than those who produce it.