Dissent 101: teaching the “dangerous knowledge” of practices of activism
Bibliographic record
Abstract
Development & Activism, a course offered at Dalhousie University, sparked controversy about whether a class should prepare students to organise activism, including public protest. Discussing these experiences, I argue there is a place in universities to teach activism as a skill of effective engagement with those in authority and with fellow citizens, thus enhancing democracy. If activism is taken as a process of commandeering space and place to engage with power structures, then the pedagogical experience is about exploring dynamic social geographies that influence, and that are influenced by, processes of organisation, manifestation and dissent. Such exploration is necessary in an era when protest is sensationalised but rarely appreciated for its complexity and when universities do not always defend an open space for progressive engagement. Résumé Un cours sur le développement et l'activisme (Development & Activism) offert à l'Université Dalhousie a suscité une controverse : faut-il préparer les étudiants à s'impliquer dans l'activisme, et même dans l'organisation de manifestations publiques? L'auteur soutient qu'il y a une place dans les universités pour l'enseignement de l'activisme comme compétence en vue d'engager efficacement les personnes en autorité et leurs concitoyens et, ainsi, de faire progresser la démocratie. Si l'activisme est compris comme un processus d'appropriation de l'espace et des lieux d'interaction avec les structures de pouvoir, l'expérience pédagogique consiste alors à explorer les influences réciproques entre les dynamiques sociogéographiques et les processus d'organisation, de protestation et de contestation. Une telle exploration est nécessaire à une époque où les manifestations sont très médiatisées, mais rarement analysées dans leur complexité, et où les universités ne contribuent pas toujours activement à la défense d'un espace public d'engagement social.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".