Products related to Bias:
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Applying Quantitative Bias Analysis to Epidemiologic Data
This textbook and guide focuses on methodologies for bias analysis in epidemiology and public health, not only providing updates to the first edition but also further developing methods and adding new advanced methods. As computational power available to analysts has improved and epidemiologic problems have become more advanced, missing data, Bayes, and empirical methods have become more commonly used.This new edition features updated examples throughout and adds coverage addressing:Measurement error pertaining to continuous and polytomous variablesMethods surrounding person-time (rate) dataBias analysis using missing data, empirical (likelihood), and Bayes methods A unique feature of this revision is its section on best practices for implementing, presenting, and interpreting bias analyses.Pedagogically, the text guides students and professionals through the planning stages of bias analysis, including the design of validation studies and the collection of validity data from other sources.Three chapters present methods for corrections to address selection bias, uncontrolled confounding, and measurement errors, and subsequent sections extend these methods to probabilistic bias analysis, missing data methods, likelihood-based approaches, Bayesian methods, and best practices.
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Unreliable : Bias, Fraud, and the Reproducibility Crisis in Biomedical Research
Reproducibility is fundamental to the scientific method.After reading a paper describing research findings, a scientist should be able to repeat the experiment and obtain the same results.Yet an alarming number—perhaps as high as 90 percent—of published biomedical research papers face challenges in independent replication.Such issues range from honest mistakes to outright fraud.The scope of this crisis, however, underscores deeper systemic issues within the scientific community: its culture, incentives, and institutions. In Unreliable, the distinguished scientist Csaba Szabo examines the causes and consequences of the reproducibility crisis in biomedical research, showing why the factors that encourage misconduct stem from flaws in real-world science.There are many culprits, including commonplace research methods and dubious statistical techniques.Academic career incentives, hypercompetition for grant funding, and a bias toward publishing positive results have exacerbated the problem.Deliberate data manipulation and fabricated findings churned out by “paper mills” are disturbingly common.Academic institutions and publishers, for their part, have perpetuated a culture of impunity. Szabo explores how these failures have hindered scientific progress and impeded the development of new treatments, and he introduces readers to the “science sleuths” who tirelessly uncover misconduct.He proposes comprehensive reforms, from scientific training to the grant system through the publication process, to address the root causes of the crisis.Written in clear language and leavened with a keen sense of irony, Unreliable is an essential account of the reproducibility crisis that gives readers an inside look at how science is actually done.
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Breaking Through Bias : Communication Techniques for Women to Succeed at Work
More than fifty years after the beginning of the Women's Movement, women are still not "making it" in traditionally male careers. Women start their careers on parity with men but generally end them far earlier, having achieved less status, lower compensation, and less satisfaction than men.Breaking Through Bias explains that it is the stereotypes about women, men, work, leadership, and family that hold women back, and it presents an integrated set of communication techniques that women can use to avoid the discriminatory consequences of these stereotypes.This highly practical book makes clear that women don't need to change who they are to succeed in their chosen careers, and they certainly don't need to act more like men.Women do, however, need to be attuned to the negative gender stereotypes that surround them; they need to anticipate the biases these stereotypes foster, and they need to manage the impressions they make to avoid or overcome these biases.Breaking Through Bias presents unique, practical, and effective advice about how women can at last break through gender bias in the workplace and win at the career advancement game.
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Anti-Bias Education for Young Children and Ourselves, Second Edition
Becoming a skilled anti-bias teacher is a journey. With this volume’s practical guidance, you’ll grow in your ability to identify, confront, and eliminate barriers of prejudice, misinformation, and bias about specific aspects of personal and social identity.Most important, you’ll find tips for helping staff and children learn to respect each other, themselves, and all people.Over the last three decades, educators across the nation and around the world have gained a wealth of knowledge and experience in anti-bias work.The result is a richer and more nuanced articulation of what is important in anti-bias education.Revolving around four core goals—identity, diversity, justice, and activism—individual chapters focus on culture and language, racial identity, family structures, gender identity, economic class, different abilities, and more.
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Who is your Blackpink bias and bias wrecker and why?
My Blackpink bias is Lisa because of her incredible stage presence, powerful dancing, and unique fashion sense. She always brings a high level of energy and charisma to their performances. My bias wrecker is Jisoo because of her stunning visuals, sweet personality, and strong vocal abilities. She has a way of capturing my attention with her charm and talent.
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What is your Itzy bias and who is your bias-wrecker?
My Itzy bias is Lia, because I love her powerful vocals and stage presence. My bias-wrecker is Yuna, because she has a captivating and charismatic aura that always catches my attention. Both of them are incredibly talented and bring something unique to the group, making it hard to choose just one favorite member!
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Who is your bias?
As an AI language model, I do not have personal preferences or biases. My purpose is to provide information and assistance to the best of my abilities without any personal inclinations.
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'Exclusion due to bias?'
Exclusion due to bias refers to the act of leaving out or discriminating against individuals or groups based on preconceived notions, stereotypes, or prejudices. This can occur in various aspects of life, such as employment, education, housing, or social interactions. Exclusion due to bias can have detrimental effects on the individuals or groups being targeted, leading to feelings of marginalization, inequality, and injustice. It is important to address and challenge bias in order to create a more inclusive and equitable society.
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Heteronormative Bias
Sexuality and Gender Now uses a psychoanalytic approach to arrive at a more informed view of the experience and relationships of those whose sexuality and gender may not align with the heterosexual "norm".This book confronts the heteronormative bias dominant in psychoanalysis, using a combination of theoretical and clinical material, offering an important training tool as well as being relevant for practicing clinicians.The contributors address the shift clinicians must make not only to support their patients in a more informed and non-prejudicial way, but also to recognise their own need for support in developing their clinical thinking.They challenge assumptions, deconstruct theoretical ideas, extend psychoanalytic concepts, and, importantly, show how clinicians can attend to their pre-conscious assumptions.They also explore the issue of erotic transference and countertransference, which, if unaddressed, can limit the possibilities for supporting patients more fully to explore their sexuality and gender.Theories of psychosexuality have tended to become split off from the main field of psychoanalytic thought and practice or read from an assumed moral high ground of heteronormativity.The book specifically addresses this bias and introduces new ways of using psychoanalytic ideas.The contributors advocate a wider and more flexible attitude to sexuality in general, which can illuminate an understanding of all sexualities, including heterosexuality. Sexuality and Gender Now will be essential reading for professionals and students of psychoanalysis who want to broaden their understanding of sexuality and gender in their clinical practice beyond heteronormative assumptions.
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Data Management in Large-Scale Education Research
Research data management is becoming more complicated.Researchers are collecting more data, using more complex technologies, all the while increasing the visibility of our work with the push for data sharing and open science practices.Ad hoc data management practices may have worked for us in the past, but now others need to understand our processes as well, requiring researchers to be more thoughtful in planning their data management routines. This book is for anyone involved in a research study involving original data collection.While the book focuses on quantitative data, typically collected from human participants, many of the practices covered can apply to other types of data as well.The book contains foundational context, instructions, and practical examples to help researchers in the field of education begin to understand how to create data management workflows for large-scale, typically federally funded, research studies.The book starts by describing the research life cycle and how data management fits within this larger picture.The remaining chapters are then organized by each phase of the life cycle, with examples of best practices provided for each phase.Finally, considerations on whether the reader should implement, and how to integrate those practices into a workflow, are discussed. Key Features:Provides a holistic approach to the research life cycle, showing how project management and data management processes work in parallel and collaborativelyCan be read in its entirety, or referenced as needed throughout the life cycleIncludes relatable examples specific to education researchIncludes a discussion on how to organize and document data in preparation for data sharing requirementsContains links to example documents as well as templates to help readers implement practices
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The Enterprise Data Catalog : Improve Data Discovery, Ensure Data Governance, and Enable Innovation
Combing the web is simple, but how do you search for data at work?It's difficult and time-consuming, and can sometimes seem impossible.This book introduces a practical solution: the data catalog.Data analysts, data scientists, and data engineers will learn how to create true data discovery in their organizations, making the catalog a key enabler for data-driven innovation and data governance. Author Ole Olesen-Bagneux explains the benefits of implementing a data catalog.You'll learn how to organize data for your catalog, search for what you need, and manage data within the catalog.Written from a data management perspective and from a library and information science perspective, this book helps you:Learn what a data catalog is and how it can help your organizationOrganize data and its sources into domains and describe them with metadataSearch data using very simple-to-complex search techniques and learn to browse in domains, data lineage, and graphsManage the data in your company via a data catalogImplement a data catalog in a way that exactly matches the strategic priorities of your organizationUnderstand what the future has in store for data catalogs
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Beat Gender Bias
Bias might be built in to how our brains work, but that doesn’t make it acceptable. When it comes to leadership, biases create a ‘sticky floor’, making it hard for women to rise to the top. An inclusive culture, by comparison, creates personal, social and economic value that will sustain an organisation’s future success. The good news is that the change to gender balance can be accelerated if you know more about how bias works. In this book, Dr Karen Morley explains how biases, particularly the insidious unconscious ones, trip us up. She outlines an approach for minimising their impact in organisations with Bias Busters – specific actions you can take with the goal of making it easier to notice, talk about and overcome bias.Beat Gender Bias is for everyone who wants work to be better – to make a difference and play a bigger, more satisfying part in creating a more inclusive world!
Price: 12.99 £ | Shipping*: 3.99 £
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What is BTS's bias?
BTS's bias refers to the member of the group that a fan favors or supports the most. Each fan may have a different bias based on their personal preferences and connections with the members. The bias can change over time as fans get to know the members better and as the group releases new music and content. Overall, BTS's bias is a personal choice and can vary among their diverse fanbase.
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What does bias mean?
Bias refers to a prejudice or inclination towards a particular perspective, idea, or group, which may result in unfair treatment or judgment. It can manifest in various forms, such as personal biases based on individual experiences or societal biases rooted in cultural norms and stereotypes. Bias can impact decision-making, behavior, and attitudes, and it is important to recognize and address biases in order to promote fairness and equality.
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Who is your bias and who is your bias-wrecker in WayV?
My bias in WayV is Ten because of his incredible dancing skills and stage presence. My bias-wrecker in WayV is Xiaojun because of his powerful vocals and charming personality. Both of them never fail to impress me with their talents and charisma.
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Who is your bias and who is your bias-wrecker in ITZY?
My bias in ITZY is Yuna. I admire her talent, charisma, and stage presence. My bias-wrecker in ITZY is Ryujin. Her powerful dance skills and unique charm always catch my attention.
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