Bibliographic record
Abstract
Youth engaged in activism are commonly portrayed as untamed, unschooled, and unable to responsibly engage in politics (Kennelly, 2011). Young people are in fact historically under-credited for their role in pushing for and obtaining positive social change (Marri & Walker, 2008). This paper presents a transformative pedagogy grounded in place developed out of the data from my dissertation research on youth developing critical civic praxis in collective community arts settings. The organizations, programs, and collectives discussed by participants had key elements in common that contributed to ongoing participation and support from the community. 1) Ongoing community engagement and community led program development. 2) Community members were trusted and encouraged to participate in organizational decisions and take on leadership roles. 3) Relationships were valued and fostered. 4) People in leadership and mentorship roles demonstrated humility, and these roles were fluid. This research was carried out in Thunder Bay, Ontario, a small urban centre of 110 000 that serves as a hub for Northwestern Ontario. I conducted qualitative interviews with key members of the arts community over a 6-month period. The theory that developed is directly rooted in the experiences of the participants.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.042 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".