Bibliographic record
Abstract
The design of their workThis is a rather special issue, as we have decided to publish three articles written by invitation by colleagues who are widely recognised in their field.They are, in order of appearance: Christine Musselin, sociologist at Sciences Po Paris and specialist in research on higher education; Erik Neveu, political scientist at Sciences Po Rennes and known for his work on social movements, gender, cultural studies, and journalism, amongst others; and André Blais, political scientist at the University of Montreal and specialist in electoral analysis and the study of public opinion.These three texts belong to the category of articles we have so far called 'What is at Stake in my Work?', in which we ask colleagues who have made what we call a fine career to reflect on the role played by methodology at key stages in their work.Until now, we have tended to spread out such contributions: Philippe Cibois' in the first issue of the new BMS, in 2018; Nonna Mayer's in the issue that followed (139); Sidney Tarrow's in 2019 and Franc ¸ois Dubet's a few months ago.We are very grateful to all seven of them for agreeing to offer an article to a modest journal such as ours.It may not seem very strategic to publish three texts by influential authors together: these have every chance of attracting a large number of readers, as those we have published previously have done.With this choice we wanted to highlight the BMS's appetite for diversity of scientific approaches and our deep commitment to methodological eclecticism.Although they received the same invitation, our three colleagues offered us texts that are wildly dissimilar, starting with their length -more than 12,000 words for Musselin and Neveu, barely over 5,000 for Blais, whose brevity is in fact deliberate.The tone is more or less sharp, the presentation of the methods implemented more or less detailed.Above all, each of them asserts different scientific choices in terms of research methods and techniques.Christine Musselin shows how her research on higher education institutions developed from a sociological approach strongly linked to a method and a research centre, themselves associated with a prestigious researcher -the sociology of organisations and the CSO, founded by Michel Crozier, in much the same vein as Franc ¸ois Dubet previously evoked the sociological intervention and Alain Touraine's team.Erik Neveu reveals methodological choices constructed voluntarily and by affinities, both positive and negative, in which the research methods are superseded by epistemological orientations.André Blais also strongly asserts his scientific convictions, albeit in a very different tone, although he champions the very methods rejected by Erik Neveu.Yet for both, methodological approaches are applied more or less independently from the type of subject covered.These articles thus feature three prestigious careers, three renowned bodies of work, three widely read and quoted researchers who have each in turn trained many colleagues.And yet, their views on the place of methodology within research and their preferences in
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.311 | 0.098 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".