Promoting Active Citizenship through the arts and youth: Canadian Youth-Led Organizations as Beacons of Hope and Transformation
Bibliographic record
Abstract
This essay details the pedagogical and cultural work of two youth-led organizations situated in Canada - Beat Nation and 411 Initiative for Change. Through the narratives generated by interviews with several of the organizations' artists and founders, the organizations‘ pedagogical work generated in cyberspace, and through artists' music, multi-media presentations, and speaking engagements in schools across Canada, we build on the critical project of reconceptualizing how youth express their awareness of what gives rise to salient social issues, such as racism, violence, environmental degradation, poverty, and gender inequalities, and how they work actively with other citizens to extend social and political rights for all. Youth-led organizations such as 411 for Change and Beat Nation seek to change the discursive realities and possibilities of hip hop by exercising it as a means of critical pedagogy. This approach supports the educational goals related to active citizenship, including solidarity, valuing the identities of minoritized populations, and a sense of belonging. We argue the organizations promote active citizenship by working to eliminate oppression confronting the global community, by guiding youth to understand the reasons for social inequality as well as the importance of working collectively to challenge injustice, and by embracing pro-social values and dispositions consistent with democracy, fairness, and equity
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.043 | 0.022 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".