A down-to-earth, practical guide for interview and participant observation and analysis. In-depth interviews and close observation are essential to the work of social scientists, but inserting one’s researcher-self into the lives of others can be daunting, especially early on. Esteemed sociologist Annette Lareau is here to help. Lareau’s clear, insightful, and personal guide is not your average methods text. It promises to reduce researcher anxiety while illuminating the best methods for first-rate research practice. As the title of this book suggests, Lareau considers listening to be the core element of interviewing and observation. A researcher must listen to people as she collects data, listen to feedback as she describes what she is learning, listen to the findings of others as they delve into the existing literature on topics, and listen to herself in order to sift and prioritize some aspects of the study over others. By listening in these different ways, researchers will discover connections, reconsider assumptions, catch mistakes, develop and assess new ideas, weigh priorities, ponder new directions, and undertake numerous adjustments—all of which will make their contributions clearer and more valuable. Accessibly written and full of practical, easy-to-follow guidance, this book will help both novice and experienced researchers to do their very best work. Qualitative research is an inherently uncertain project, but with Lareau’s help, you can alleviate anxiety and focus on success.

本书共五章，按科学研究的顺序展开，结合图片及生动的案例，系统地阐述了科学探索的本质与意义、如何确定选题、研究中如何高效开展实验、如何总结实验并进行论文写作、如何避免写作中的常见问题等。

Charles C. Ragin’s The Comparative Method proposes a synthetic strategy, based on an application of Boolean algebra, that combines the strengths of both qualitative and quantitative sociology. Elegantly accessible and germane to the work of all the social sciences, and now updated with a new introduction, this book will continue to garner interest, debate, and praise.

From two experts in the field comes an accessible, how-to guide that will help researchers think more productively about the relation between theory and data at every stage of their work. In Data Analysis in Qualitative Research, Iddo Tavory and Stefan Timmermans provide a how-to guide filled with tricks of the trade for researchers who hope to take excellent qualitative data and transform it into powerful scholarship. In their previous book, Abductive Analysis: Theorizing Qualitative Research, Timmermans and Tavory offered a toolkit for innovative theorizing in the social sciences. In this companion, they go one step further to show how to uncover the surprising revelations that lie waiting in qualitative data—in sociology and beyond. In this book, they lay out a series of tools designed to help both novice and expert scholars see and understand their data in surprising ways. Timmermans and Tavory show researchers how to “stack the deck” of qualitative research in favor of locating surprising findings that may lead to theoretical breakthroughs, whether by engaging with theory, discussing research strategies, or walking the reader through the process of coding data. From beginning to end of a research project, Data Analysis in Qualitative Research helps social scientists pinpoint the most promising paths to take in their approach.

Scientific writing is often dry, wordy, and difficult to understand. But, as Anne E. Greene shows in Writing Science in Plain English,writers from all scientific disciplines can learn to produce clear, concise prose by mastering just a few simple principles. This short, focused guide presents a dozen such principles based on what readers need in order to understand complex information, including concrete subjects, strong verbs, consistent terms, and organized paragraphs. The author, a biologist and an experienced teacher of scientific writing, illustrates each principle with real-life examples of both good and bad writing and shows how to revise bad writing to make it clearer and more concise. She ends each chapter with practice exercises so that readers can come away with new writing skills after just one sitting. Writing Science in Plain English can help writers at all levels of their academic and professional careers―undergraduate students working on research reports, established scientists writing articles and grant proposals, or agency employees working to follow the Plain Writing Act. This essential resource is the perfect companion for all who seek to write science effectively.

A trusted editor turns his attention to the most important part of writing: revision. So you’ve just finished writing something? Congratulations! Now revise it. Because revision is about getting from good to better, and it’s only finished when you decide to stop. But where to begin? In On Revision, William Germano shows authors how to take on the most critical stage of writing anything: rewriting it. For more than twenty years, thousands of writers have turned to Germano for his insider’s take on navigating the world of publishing. A professor, author, and veteran of the book industry, Germano knows what editors want and what writers need to know: Revising is not just correcting typos. Revising is about listening and seeing again. Revising is a rethinking of the principles from the ground up to understand why the writer is doing something, why they’re going somewhere, and why they’re taking the reader along with them. On Revision steps back to take in the big picture, showing authors how to hear their own writing voice and how to reread their work as if they didn’t write it. On Revision will show you how to know when your writing is actually done—and, until it is, what you need to do to get it there.

Drawing on more than four decades of experience as a researcher and teacher, Howard Becker now brings to students and researchers the many valuable techniques he has learned. Tricks of the Trade will help students learn how to think about research projects. Assisted by Becker's sage advice, students can make better sense of their research and simultaneously generate fresh ideas on where to look next for new data. The tricks cover four broad areas of social science: the creation of the "imagery" to guide research; methods of "sampling" to generate maximum variety in the data; the development of "concepts" to organize findings; and the use of "logical" methods to explore systematically the implications of what is found. Becker's advice ranges from simple tricks such as changing an interview question from "Why?" to "How?" (as a way of getting people to talk without asking for a justification) to more technical tricks such as how to manipulate truth tables. Becker has extracted these tricks from a variety of fields such as art history, anthropology, sociology, literature, and philosophy; and his dazzling variety of references ranges from James Agee to Ludwig Wittgenstein. Becker finds the common principles that lie behind good social science work, principles that apply to both quantitative and qualitative research. He offers practical advice, ideas students can apply to their data with the confidence that they will return with something they hadn't thought of before. Like Writing for Social Scientists, Tricks of the Trade will bring aid and comfort to generations of students. Written in the informal, accessible style for which Becker is known, this book will be an essential resource for students in a wide variety of fields. "An instant classic. . . . Becker's stories and reflections make a great book, one that will find its way into the hands of a great many social scientists, and as with everything he writes, it is lively and accessible, a joy to read."—Charles Ragin, Northwestern University

是否有不同的方式來教與學社會學？如何讓學生在實做中同時習得研究的技法與精湛的論點？如何培養學生提出兼具本地特色與理論意涵的問題？是否可能將社會學本身的信念融入社會學的教學之中？ 田野工作者以自身當做探索社會生活的媒介，觸動其中的關鍵機制，這是以身為度。因此，田野工作不僅僅蒐集與創造資料，同時也切磋與創新理論、反省社會學知識的認識論、以及呈現各種生命情調相互激盪的存在論。在教學上，師生以各自的研究與經驗為例交流，也是以身為度。 本書提供八個田野工作的實例（一個老師，七個學生）以及一篇對田野工作教學的考察與反省。這些實例採取了參與實作、參與觀察、深度訪談等技法，處理了資本主義的在地呈現、成人、成家、立業、上班、購物與飲食等課題。整本書兼具在地的觸感與理論的意涵，同時也呈現了學術與生命的交融，這是深刻與原創的學術研究的前提。 本書不只是在討論「田野工作」，同時也觸及了「如何做深刻的社會分析」。誠摯邀請你－－敬愛的讀者－－一起經歷這個生猛活潑、認真踏實、結合了個人傳記與集體關懷的台灣社會探險之旅！

Most textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is about using regression to solve real problems of comparison, estimation, prediction, and causal inference. Unlike other books, it focuses on practical issues such as sample size and missing data and a wide range of goals and techniques. It jumps right in to methods and computer code you can use immediately. Real examples, real stories from the authors' experience demonstrate what regression can do and its limitations, with practical advice for understanding assumptions and implementing methods for experiments and observational studies. They make a smooth transition to logistic regression and GLM. The emphasis is on computation in R and Stan rather than derivations, with code available online. Graphics and presentation aid understanding of the models and model fitting.

Conventional understanding of what it means to "explain" something in the social sciences provokes unnecessary confusion and conflict, and indeed is often based more on analysts' imaginations than actors' realities. The Explanation of Social Action lays out a sustained critique of this understanding, pointing out that the root of the problem is an attempt to counterpose two radically different types of answers to the question of why someone did a certain thing--first person responses and third person ones. John Levi Martin illustrates how this tendency is epitomized in attempts to explain human action in "causal" terms. He shows how this causality has little to do with the real world, but instead involves the creation of imaginary worlds, stemming from an intellectual history whereby social scientists began to distrust the self-understanding of actors and accepted fundamentally anti-democratic epistemologies, due to an epistemic hiatus in social knowledge and the adoption of practices in the intensely hierarchic setting of forced incarceral institutions for the insane. Martin moves on to highlight other traditions that do not assume that the cognitive schemes of actors are fundamentally arbitrary. These traditions in turn suggest that the analytic problems that now arise require attention to the nature of judgment, implying the need for an understanding of the process whereby actors intuit intersubjectively valid qualities of complex social objects. Tackling the very way in which social scientists analyze why people do things, The Explanation of Social Action is a novel and essential take on the evidence on which their explanations are based.

This book presents the first broad look at the rapidly emerging field of data-intensive science, with the goal of influencing the worldwide scientific and computing research communities and inspiring the next generation of scientists. Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud-computing technologies. This collection of essays expands on the vision of pioneering computer scientist Jim Gray for a new, fourth paradigm of discovery based on data-intensive science and offers insights into how it can be fully realized.

做社会学研究，非常不容易。如果不明了自身所做之事，不明了工作的努力方向，你就会像瓷器店里的公牛一样，必然把事情搞砸。这是约翰·李维·马丁在这本如何进行严谨的社会科学研究的书中告诫我们的，它风趣、睿智而必需。本书关注的是研究者需要进行的各种实际决策：到哪儿去找寻你所需要的资料？你所找到的资料与可能收集到的资料整体之间有何种关联？ 这是一本社会科学的用户指南，既适用于本科生，也适用于研究生。作者不是仅仅提供一些机械的规则与应用，而是与读者一起对于方法问题进行通透的思考。他承认研究者也是人，因此也会像研究对象一样受制于同样的认知局限与扭曲，进而提出克服和弥补上述局限的办法。马丁论证了自律的重要性，说明学术伦理上出问题必将导致研究本身出问题，反之亦然。本书是一本里程碑式的作品；在社会学研究的过程中，学生们会反复从中受到启迪。

融通，关乎人类历史，更关乎人类未来。今天的文化积累已让人类拥有可以改变自身生物本性的力量，以科学探究人性奥秘的新时代已到来。在一个更广阔的时空背景下，人性与文化、自我与社会都将被重新定义。威尔逊以无与伦比的雄心壮志提出融通计划，坚信它将赋予未来人类一种分析和预测的强大力量，让我们有能力应对即将到来的巨变。 这是一场浩大的知识历险。从大脑中的化学反应，到文化的基因基础，从颜色语言受到的遗传学限制，到《洛丽塔》中蕴含的生物学原则…爱德华·威尔逊轻松跨越科学与人文的鸿沟，自如穿梭于物理学、人类学、心理学、哲学、宗教、伦理与艺术等各领域间。这位殿堂级的科学大师用清晰、雄辩的文字， 将人类知识的新进展巧妙地编织到了一起，完成了这部博大精深又妙趣横生的著作。站在“巨人”的肩膀上，我们才能登上知识的巅峰，将今日破碎的知识风景尽收眼底。读过此书，我们将以全新的方式理解知识。 这是一部我们时代里程碑式的著作，融通的构想也必将成为人类认识自身与世界的一个新起点。威尔逊对未来世代知识图景的大胆想象，凝聚了他毕生对人类、知识和社会进化的深刻思考，极具独创性和启发性。每一位善于思考、关心未来的读者都应该认真聆听。

法国人凭其新发现的词源学热情创造了“叙事学”(narratologie)这一词语，用以指研究叙事结构的学问。英美知识界颇怀疑于“一0logy”的大胆运用，也许不无道理。不过，名称问题不应与话题的合法性相混淆。尽管关于长篇小说、史诗、短篇小说、民间传说、寓言等具体文类的研究著作汗牛充栋，但从总体上讨论叙事学科的英语论著却极少。除体裁区别的分析以外，还有对于“叙事本质上是什么”这一问题的界定。文学批评家们太过倾向于单独地考虑文字媒介，尽管他们每天都通过电影、滑稽连环画、绘画、雕塑、舞剧与音乐来消费故事。在这些人工制品之间必定有某些亚层次是共同的，否则我们无法解释《睡美人》如何能被改编成电影、芭蕾舞剧或哑剧表演。 本书在有效综合俄国、法国、英美的符号学、语言学、叙事学等各种相关理论的基础上，着眼于广义“叙事”(包括各种媒介的叙事，尤其是小说与电影两大媒介)，对“故事”与“话语”两大范畴进行了严格区分和细密论证，从而廓清了一般叙事之结构。导论部分由“表达／内容”与“质料／形式”的纵横交叉，区分出“表达的形式与质料”和“内容的形式与质料”，进而厘定了“故事(内容)”与“话语(表达)”各自的涵盖领域。第二、第三两章是关于“故事”的具体展开，分别对“事件”与“实存”两方面加以论证。第四、第五两章则是关于“话语”的具体展开，对“非叙述”与“叙述者”的若干形式进行了精细区别和论证。结语部分给出了“叙事结构示意图”。该书在叙事理论史上具有广泛影响，其中的“叙事一交流情境示意图”与“叙事结构示意图”被频繁征引、讨论。它对于叙事学、小说理论、影视美学等领域的学者都有重要的参考价值。

Written with students in mind, Thinking Through Theory explores the role of theory in sociology with a focus on good thinking: how to keep from thinking in circles, how to know when we are contradicting ourselves, and how to avoid thinking tautologies are meaningful.

Sociological research is hard enough already you don't need to make it even harder by smashing about like a bull in a china shop, not knowing what you're doing or where you're heading. Or so says John Levi Martin in this witty, insightful, and desperately needed primer on how to practice rigorous social science. Thinking Through Methods focuses on the practical decisions that you will need to make as a researcher where the data you are working with comes from and how that data relates to all the possible data you could have gathered. This is a user's guide to sociological research, designed to be used at both the undergraduate and graduate level. Rather than offer mechanical rules and applications, Martin chooses instead to team up with the reader to think through and with methods. He acknowledges that we are human beings and thus prone to the same cognitive limitations and distortions found in subjects and proposes ways to compensate for these limitations. Martin also forcefully argues for principled symmetry, contending that bad ethics makes for bad research, and vice versa. Thinking Through Methods is a landmark work one that students will turn to again and again throughout the course of their sociological research.

在2002年一篇曾引发数学界巨大反响的文章《一个数学家的叹息》中，保罗·洛克哈特猛烈抨击了美国中小学数学教育的现状：学生只是被要求记住公式，并在练习题中反复套用，而这一创造性过程应有的兴奋、喜悦乃至痛苦和挫败却不见了。 在洛克哈特看来，数学是一门艺术，而老师教授数学的方法应该是，向学生诚实地传递自己对于这门学科的热爱，激发和激励他们与生俱来的好奇心，并帮助和引导他们实际投身到这段迷人的旅途中去。 本书正是洛克哈特这一思想的体现。他对数学的热爱在字里行间显露无遗，同时他也不讳言旅途的艰难。本书分为两个部分，分别介绍了对形状和运动的度量。他以平实的语言将几何学和微积分的复杂概念以及两者之间的精妙关联解释得清晰易懂，生动展示了数学家都在做什么，以及他们为什么要这么做。

Today’s researchers have access to more information than ever before. Yet the new material is both overwhelming in quantity and variable in quality. How can scholars survive these twin problems and produce groundbreaking research using the physical and electronic resources available in the modern university research library? In Digital Paper, Andrew Abbott provides some much-needed answers to that question. Abbott tells what every senior researcher knows: that research is not a mechanical, linear process, but a thoughtful and adventurous journey through a nonlinear world. He breaks library research down into seven basic and simultaneous tasks: design, search, scanning/browsing, reading, analyzing, filing, and writing. He moves the reader through the phases of research, from confusion to organization, from vague idea to polished result. He teaches how to evaluate data and prior research; how to follow a trail to elusive treasures; how to organize a project; when to start over; when to ask for help. He shows how an understanding of scholarly values, a commitment to hard work, and the flexibility to change direction combine to enable the researcher to turn a daunting mass of found material into an effective paper or thesis. More than a mere how-to manual, Abbott’s guidebook helps teach good habits for acquiring knowledge, the foundation of knowledge worth knowing. Those looking for ten easy steps to a perfect paper may want to look elsewhere. But serious scholars, who want their work to stand the test of time, will appreciate Abbott’s unique, forthright approach and relish every page of Digital Paper.

Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as economics, sociology, public policy, and data science. Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the R programming language and to interpret the results—it encourages hands-on learning, not paper-and-pencil statistics. More than forty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior. Proven in the classroom, this one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, and also comes with supplementary teaching materials for instructors. Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data science Provides hands-on instruction using R programming, not paper-and-pencil statistics Includes more than forty data sets from actual research for students to test their skills on Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools Features a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercises Offers a solid foundation for further study Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides