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Обычная версия сайта
Бакалавриат 2019/2020

Научно-исследовательский семинар

Язык: английский
Кредиты: 2

Course Syllabus

Abstract

The research seminar aims at helping students in their scientific and research activities, by mastering their knowledge in research design formulation, as well as new research methods application. The first part of the course deals with the basics of the research: research design composition, literature review, theory and method selection, as well as research strategies. In the second part of the course student practice one of the methods (Ethnography, Qualitative Comparative Analysis (QCA) or Text – as – Data techniques) by discussing their peculiarities and developing their own projects.
Learning Objectives

Learning Objectives

  • Develop students' skills in formulating and justifying their research designs
  • Master students' capabilities to develop and implement various research strategies
  • Acquaint students with the selected method of research (Ethnography, QCA, Text-as-Data) and their applications
Expected Learning Outcomes

Expected Learning Outcomes

  • Able to perform empirical data analysis using the selected method
  • Able to formulate and present results of the research based on the selected method
  • Enumerates and characterizes the basic elements of research
  • Formulates and justifies the research design and its key components
  • Able to select and overview scientific literature to characterize a research field
  • Compares and characterises the basic research strategies
  • Able to define the basic principles and peculiarities of the selected research method (ethnography, QCA, text mining)
  • Able to perform data collection and preparation for the analysis using the selected research method
  • Able to develop a research design and research strategy using the selected method
  • Able to interpret the results of the research using the selected method, highlighting its strengths and weaknesses
Course Contents

Course Contents

  • Seminar 1.1. Basics of the Research. Research Questions.
    The basics of research and inference in political science. Formal requirements to the course papers. Plagiarism. Algorithm and strategy of research. Research question types. Hints for “good” research questions.
  • Seminar 1.2. Selecting and Overviewing Literature.
    Refining and framing the research question. Literature selection methods. Overview of the sources of scientific literature.
  • Seminar 1.3. Literature Reviews
    Annotated bibliography. Types and strategies of the literature review. Defining puzzles, research gaps and academic debates. Motivation and state-of-the-art.
  • Seminar 1.4. Developing a Research Design
    Specifying the research design. Theories, frameworks and models. Hypotheses and variables. Conceptualization, operationalization and measurement.
  • Seminar 1.5. Research Strategies, Methods and Data
    Research strategies. Case studies, small-N and large-N strategies. Qualitative and quantitative data and research methods: pros and cons. Possible sources of the empirical data.
  • Seminar 2.1.
    2.1:Introduction to ethnography: Ethnography in the family of “qualitative” methods. Ethnographic traditions and schools in anthropology and sociology (British, American and French research traditions). Principal research methods: (participant) observation, fieldnote writing, ethnographic interviewing. Methodology. Role of the researcher: “ethnographic comportment”. Sensibility. (Self)-reflexivity. Ethnographic immersion (and the study of politics). 2.2 :Introduction: The logic of sets according to Ch. Ragin. Necessary and sufficient conditions. Advantages and assumptions of QCA.; 2.3: Introduction. Digital Footprint Data. Structure of Scientific Articles.: Consideration of various data sources in digital environment. The role of data in scientific articles.
  • Seminar 2.2
    2.1:Two traditions of (political) ethnography: Interpretivist vs. (neo)positivist epistemology. Standpoints and worldviews. Realist tradition. Advancing truth-claims. Interpretive tradition. Post-modern anthropological thinking on ethnography. Limits of interpretation. 2.2 :Boolean Algebra in Comparative Analysis: Boolean algebra, conjunction, disjunction procedures, logical OR and AND. Truth tables. Variables’ presentation.; 2.3: Data Collection: structural data (Data Miner): Data Miner is a Google Chrome extension that helps you scrape data from web pages and into a CSV file or Excel spreadsheet. URL: https://data-miner.io/
  • Seminar 2.3
    2.1:Two traditions of (political) ethnography: “Ethnography lite”. Studying “high” and “low” politics through ethnography. Ethnography in policy studies. Ethnography in post-colonial and (critical) development studies. 2.2 :The Power of QCA in Political Science (classification, hypotheses): Classifications, hypotheses. Minimization procedures. Causal mechanisms. Using software for QCA.; 2.3: Data Collection: SNS data (Popsters): Popsters helps to compare and measure efficiency of posts of any page that you are interested in. URL: https://popsters.us/
  • Seminar 2.4
    2.1:Ethnographic research design: Practices of ethnographic research. Strategy and improvisation. Emic/etic. The field. Making research choices. 2.2 :The Power of QCA in Political Science (classification, hypotheses): Calibration, the necessity of exogenous criteria. Choosing variables.; 2.3: Introduction: Text Mining. Features of text data.: Lexicon. Frequency analysis of texts. Zipf's law. Data preparation. Morphological analysis. Stamping and Lemmatization.
  • Seminar 2.5
    2.1:Ethnographic research design: Major “stumbling blocks” in the research process: (1) selecting a research topic; (2) identifying research locations/settings/sites; (3) data collection: positionality, fieldnote writing and interviewing; (4) data analysis: techniques and sensibilities. 2.2 :The Power of QCA in Political Science (classification, hypotheses): Working with reminders, controversies and missings.; 2.3: Feature engineering: Regular expressions & Text classification.: Feature engineering. Prediction of attributes by words and features. Algorithms of classification. Naive Bayes. Regression Models.
  • Seminar 2.6
    2.1:In the field: Discovering the field: problems of getting in and out of (multiple) fieldwork locations. Methods planned and methods used: adjusting research strategy in the field 2.2 :Testing Hypotheses in R: Calibrating and recalibrating data. Rules of establishing thresholds.; 2.3: Identifying Characteristic Words: Log-likelihood.: Compares the appearance of a word indifferent collections.
  • Seminar 2.7
    2.1:In the field: “No result” as a result. Problems of access. Relationships to/with “informants”. Feedback. Fear. Surprise. Safety and security. 2.2 :Testing Hypotheses in R: Testing hypotheses practice 1; 2.3: Identifying Characteristic Words: Log-likelihood.: Log-Likelihood: G-squared. Effect size: Log odds ratio.
  • Seminar 2.8
    2.1:Writing up ethnographic methodologies: Presenting ethnographic methodologies. Contextualizing the researcher and the experiences of research (in the field). Description of research steps, context and conditions of the fieldwork. Feminist research. Controversies. 2.2 :Testing Hypotheses in R: Testing hypotheses practice 2; 2.3: Collocations & PMI: Co-occurrence. N-grams. Methods for detecting collocations. “bag of words” model. Collocation measure. logDice. Pointwise Mutual Information Of Pairs Of Items (PMI).
  • Seminar 2.9
    2.1:Writing up ethnographic methodologies: Ethnographic self-consciousness: partiality, reflexivity, critical standpoint, collaborative and action research. Examples of methodological discussions from (political) ethnographies. 2.2 :Testing Hypotheses in R: Testing hypotheses practice 3; 2.3: Semantic Networks and SNA: Semantic Networks. Latent semantic analysis (LSA).
  • Seminar 2.10
    2.1:Writing up research findings: Ethnographic writing process: “organizational approach” and “evocative approach”. Data organization. Research reporting. Theme development. Empirical precision and its absence. 2.2 :Testing Hypotheses in R: Testing hypotheses practice 4; 2.3: Semantic Networks and SNA: SNA practice 1
  • Seminar 2.11
    2.1:Writing up research findings: Example selection. Vignettes. Extended examples. Linking ethnography and theory. 2.2 :A Variety of QCA Techniques: MVQSA, FSQCA.: MVQSA, FSQCA; working with non-dichotomous variables.; 2.3: Semantic Networks and SNA: SNA practice 2
  • Seminar 2.12
    2.1:Writing up research findings: The author in the text. Sensibilities. Caveats. 2.2 :Fuzzy Sets: Working with fuzzy sets. Measures of Consistency and Coverage.; 2.3: Topic Modeling (LDA): The operationalization of the "topic" concept as a probability distribution vocabulary. Latent Dirichlet allocation (LDA).
  • Seminar 2.13
    2.1:Discussion and evaluation: Research paradigms and evaluative standards. “Good work” in ethnography. Evaluation and accountability: credibility, coherence, transparency, impact, worthiness. 2.2 :Fuzzy Sets: Fuzzy sets practice; 2.3: Topic Modeling (LDA): LDA practice
  • Seminar 2.14
    2.1:Discussion and evaluation: Research “objects” versus research “stakeholders”. Researched community and feedback. 2.2 :Presentation of Students’ Projects: Students are expected to present their own projects based on their own data and results obtained from the analysis in QCA GUI in R.; 2.3: Presentation of Students’ Projects: Students are expected to present group projects based on their own text data and results obtained from the analysis in R.
  • Seminar 2.15
    2.1:Discussion and evaluation: Research ethics. Collaborative spirit in ethnography of politics/policy. 2.2 :Presentation of Students’ Projects: Students are expected to present their own projects based on their own data and results obtained from the analysis in QCA GUI in R.; 2.3: Presentation of Students’ Projects: Students are expected to present group projects based on their own text data and results obtained from the analysis in R.
Assessment Elements

Assessment Elements

  • non-blocking In-class participation
    Participation in seminar workshops and contribution to seminar discussions, based on the mandatory readings. In-class participation is evaluated throughout the whole course, hence 25 per cent of the grade comes from the first part of the course and 75 per cent – from the second part.
  • non-blocking Final Paper
    A written group assignment (can be done individually upon request from a student), evaluating students’ progress during the second part of the course. The content of the assignment depends on which track from part 2 is chosen.
  • non-blocking Research Proposal
    A research proposal is handed in and assessed in parts, as a home assignment for each of the seminar in Part 1. The final grade for the component is calculated as an average of all marks for the home assignments.
  • non-blocking Examination
    The exam is held in a written (test) format in the LMS (https://lms.hse.ru/) and Zoom (https://zoom.us/). The exam last for 1 hour 20 minutes. Students should log in to the Zoom and the LMS 5 minutes before the start of the exam, using the computer that has a web-camera and a microphone. To participate in the exam, a student must: (1) switch on a web-camera and a microphone in the Zoom and keep them on during the entire exam; (2) follow the lecturer’s instructions to open the test in the LMS; (3) start doing the test in the LMS. During the exam students are not allowed to (1) switch off a web-camera or a microphone in the Zoom; (2) open pages in a web-browser other that the test in the LMS; (3) use any additional printed and / or electronic materials and devices (e.g. smartphones). A short-term connection problem can last no more than 5 minutes and can occur not more than 2 times during the exam. A long-term connection problem is more than 5 minutes, or more than two short-term connection problems. In case of long-term connection problems students cannot proceed with the exam and must retake it in the same format.
Interim Assessment

Interim Assessment

  • Interim assessment (4 module)
    0.25 * Examination + 0.25 * Final Paper + 0.25 * In-class participation + 0.25 * Research Proposal
Bibliography

Bibliography

Recommended Core Bibliography

  • Approaches and methodologies in the social sciences : a pluralist perspective / ed. by Donatella della Porta . (2008). Cambridge [u.a.]: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.283822104
  • Bamman, D., Eisenstein, J., & Schnoebelen, T. (2014). Gender identity and lexical variation in social media[The resear]. Journal of Sociolinguistics, 18(2), 135–160. https://doi.org/10.1111/josl.12080
  • Geddes, B. (DE-588)171415787, (DE-576)132211866. (2003). Paradigms and sand castles : theory building and research design in comparative politics / Barbara Geddes. Ann Arbor, Mich.: University of Michigan Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.104638176
  • Leavy, P. (2014). The Oxford Handbook of Qualitative Research. Oxford: Oxford University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=779511
  • Mahoney, J. (2003). Long-Run Development and the Legacy of Colonialism in Spanish America. American Journal of Sociology, 109(1), 50–106. https://doi.org/10.1086/378454
  • Nguyen, D., Gravel, R., Trieschnigg, D., & Meder, T. (2013). “How old do you think I am?” A study of language and age in Twitter. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.E50BF78
  • Però, D., Wright, S., & Shore, C. (2011). Policy Worlds : Anthropology and the Analysis of Contemporary Power. New York: Berghahn Books. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=416088
  • Ragin, C. C. (2013). The Comparative Method : Moving Beyond Qualitative and Quantitative Strategies. Oakland, California: University of California Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=784602
  • Schwartz-Shea, P., & Yanow, D. (2006). Interpretation and Method : Empirical Research Methods and the Interpretive Turn. Armonk, N.Y.: ME Sharpe, Inc. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=199779
  • Silge, J., & Robinson, D. (2017). Text Mining with R : A Tidy Approach (Vol. First edition). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=1533983

Recommended Additional Bibliography

  • Bekmurzaev, N., Lottholz, P., & Meyer, J. (2018). Navigating the safety implications of doing research and being researched in Kyrgyzstan: cooperation, networks and framing. Central Asian Survey, 37(1), 100–118. https://doi.org/10.1080/02634937.2017.1419165
  • Beyer, J., Rasanayagam, J., & Reeves, M. (2013). Ethnographies of the State in Central Asia : Performing Politics. Bloomington: Indiana University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=677473
  • Gorgadze Aleksey, & Kolycheva Alina. (n.d.). Mapping Ideas: Semantic Analysis of “Postnauka” Materials. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsclk&AN=edsclk.https%3a%2f%2fcyberleninka.ru%2farticle%2fn%2fmapping-ideas-semantic-analysis-of-postnauka-materials
  • Levy, J. S. (2008). Case Studies: Types, Designs, and Logics of Inference. Conflict Management & Peace Science, 25(1), 1–18. https://doi.org/10.1080/07388940701860318
  • Mosse, D. (2005). Cultivating Development : An Ethnography of Aid Policy and Practice. London: Pluto Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=167913
  • Munzert, S. (2014). Automated Data Collection with R : A Practical Guide to Web Scraping and Text Mining. HobokenChichester, West Sussex, United Kingdom: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=878670
  • Seawright, J., & Gerring, J. (2008). Case Selection Techniques in Case Study Research: A Menu of Qualitative and Quantitative Options. Political Research Quarterly, 61(2), 294–308. https://doi.org/10.1177/1065912907313077
  • William Q Judge, Stav Fainshmidt, & J Lee Brown III. (2014). Which model of capitalism best delivers both wealth and equality? Journal of International Business Studies, (4), 363. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.pal.jintbs.v45y2014i4p363.386