How institutionalisation of a movement fosters protest: The case of student protests in France
Bibliographic record
Abstract
Abstract This paper explains how institutionalisation can go hand in hand with the use of more disruptive tactics by social actors. Inspired by a feminist conceptualisation of the social movement institutionalisation process, we adopt a fluid definition of the state–society division and attend to how institutional actors and groups negotiate their relationships at different scales of protest. To illustrate our argument, we take a closer look at the student movement in France. Based on the analysis of higher education policies between 2005 and 2016, and 16 semi-structured interviews conducted with key actors, we identify a process of partial institutionalisation whereby student organisations are regulated by different material conditions depending on the scale of protest. These material conditions, translated through institutional arrangements, shape the ways in which student organisations build identity boundaries among them, thereby leading to the use of different tactics of protest.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.023 | 0.028 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".