Download Free The Bias Of Science Book in PDF and EPUB Free Download. You can read online The Bias Of Science and write the review.

This book is intended as an introduction to a wide variety of biases affecting human cognition, with a specific focus on how they affect scientists and the communication of science. The role of this book is to lay out how these common biases affect the specific types of judgements, decisions and communications made by scientists.
Why we don't live in a post-truth society but rather a myside society: what science tells us about the bias that poisons our politics. In The Bias That Divides Us, psychologist Keith Stanovich argues provocatively that we don't live in a post-truth society, as has been claimed, but rather a myside society. Our problem is not that we are unable to value and respect truth and facts, but that we are unable to agree on commonly accepted truth and facts. We believe that our side knows the truth. Post-truth? That describes the other side. The inevitable result is political polarization. Stanovich shows what science can tell us about myside bias: how common it is, how to avoid it, and what purposes it serves. Stanovich explains that although myside bias is ubiquitous, it is an outlier among cognitive biases. It is unpredictable. Intelligence does not inoculate against it, and myside bias in one domain is not a good indicator of bias shown in any other domain. Stanovich argues that because of its outlier status, myside bias creates a true blind spot among the cognitive elite--those who are high in intelligence, executive functioning, or other valued psychological dispositions. They may consider themselves unbiased and purely rational in their thinking, but in fact they are just as biased as everyone else. Stanovich investigates how this bias blind spot contributes to our current ideologically polarized politics, connecting it to another recent trend: the decline of trust in university research as a disinterested arbiter.
On topics from genetic engineering and mad cow disease to vaccination and climate change, this Handbook draws on the insights of 57 leading science of science communication scholars who explore what social scientists know about how citizens come to understand and act on what is known by science.
This is the first book-length introductory study of the concept of a created scientific controversy, providing a comprehensive and wide-ranging analysis for students of philosophy of science, environmental and health sciences, and social and natural sciences.
The United States economy relies on the productivity, entrepreneurship, and creativity of its people. To maintain its scientific and engineering leadership amid increasing economic and educational globalization, the United States must aggressively pursue the innovative capacity of all its people—women and men. However, women face barriers to success in every field of science and engineering; obstacles that deprive the country of an important source of talent. Without a transformation of academic institutions to tackle such barriers, the future vitality of the U.S. research base and economy are in jeopardy. Beyond Bias and Barriers explains that eliminating gender bias in academia requires immediate overarching reform, including decisive action by university administrators, professional societies, federal funding agencies and foundations, government agencies, and Congress. If implemented and coordinated across public, private, and government sectors, the recommended actions will help to improve workplace environments for all employees while strengthening the foundations of America's competitiveness.
Anthropic Bias explores how to reason when you suspect that your evidence is biased by "observation selection effects"--that is, evidence that has been filtered by the precondition that there be some suitably positioned observer to "have" the evidence. This conundrum--sometimes alluded to as "the anthropic principle," "self-locating belief," or "indexical information"--turns out to be a surprisingly perplexing and intellectually stimulating challenge, one abounding with important implications for many areas in science and philosophy. There are the philosophical thought experiments and paradoxes: the Doomsday Argument; Sleeping Beauty; the Presumptuous Philosopher; Adam & Eve; the Absent-Minded Driver; the Shooting Room. And there are the applications in contemporary science: cosmology ("How many universes are there?", "Why does the universe appear fine-tuned for life?"); evolutionary theory ("How improbable was the evolution of intelligent life on our planet?"); the problem of time's arrow ("Can it be given a thermodynamic explanation?"); quantum physics ("How can the many-worlds theory be tested?"); game-theory problems with imperfect recall ("How to model them?"); even traffic analysis ("Why is the 'next lane' faster?"). Anthropic Bias argues that the same principles are at work across all these domains. And it offers a synthesis: a mathematically explicit theory of observation selection effects that attempts to meet scientific needs while steering clear of philosophical paradox.
Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts. The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management. Walks you through every step of carrying out a meta-analysis in ecology and evolutionary biology, from problem formulation to result presentation Brings together experts from a broad range of fields Shows how to avoid, minimize, or resolve pitfalls such as missing data, publication bias, varying data quality, nonindependence of observations, and phylogenetic dependencies among species Helps you choose the right software Draws on numerous examples based on real biological datasets
It seems like most of what we read about the academic social sciences in the mainstream media is negative. The field is facing mounting criticism, as canonical studies fail to replicate, questionable research practices abound, and researcher social and political biases come under fire. In response to these criticisms, Matt Grossmann, in How Social Science Got Better, provides a robust defense of the current state of the social sciences. Applying insights from the philosophy, history, and sociology of science and providing new data on research trends and scholarly views, he argues that, far from crisis, social science is undergoing an unparalleled renaissance of ever-broader understanding and application. According to Grossmann, social science research today has never been more relevant, rigorous, or self-reflective because scholars have a much better idea of their blind spots and biases. He highlights how scholars now closely analyze the impact of racial, gender, geographic, methodological, political, and ideological differences on research questions; how the incentives of academia influence our research practices; and how universal human desires to avoid uncomfortable truths and easily solve problems affect our conclusions. Though misaligned incentive structures of course remain, a messy, collective deliberation across the research community has shifted us into an unprecedented age of theoretical diversity, open and connected data, and public scholarship. Grossmann's wide-ranging account of current trends will necessarily force the academy's many critics to rethink their lazy critiques and instead acknowledge the path-breaking advances occurring in the social sciences today.