Feminist Internships and the Depression of Political Imagination: Implications for Women's Studies
Bibliographic record
Abstract
Scholars have paid ample attention to many of the effects of the institutionalization of the women's movement, but have not sufficiently attended to how such formalization has affected younger generations' perceptions of what it means to be politically active. The article uses interviews with an ethnically and racially diverse sample of Canadian university students who interned in feminist organizations to better understand their perceptions. The authors found the "feminist internship" to have predictable features that depress students' understanding of the kind of social change or challenges that are possible, and that train them to think of activism as another form of paid employment—a process the authors refer to as the routinization of political consciousness. Significantly, too, they found the likening of activism to work has also transformed social interactions among generations in the movement, replacing conflict and contestation about political goals and means with a script akin to employer/employee relations. Despite the trend towards formalization, students in the study most valued organizations in which staff members broke rules, attended to political ethics, eschewed hierarchy, strove for transparency, and openly debated ideas, signaling that de-professionalization may be a sound strategy for producing more movement adherents from emerging generations. Finally, the article reflects upon the role of women's studies units in brokering these relations between students and organizations, explicating how internships also lead students to revise their conceptions of women's studies curriculum as impractically critical and utopian.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.069 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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".