Peace Together: Collaborative Research Towards a Human Rights Youth Strategy in Teaching and Teacher Education
Bibliographic record
Abstract
This paper describes a research collaborative network consisting of: two district school boards in southern Ontario and eastern Ontario; a university faculty of education and social justice institute; a regulatory professional standards organization; and, a non-profit prosperity organization. The collaborative seeks to enhance public confidence and awareness on the importance of a human rights framework for youth in teaching and teacher education. The research is guided by three principles: changing mindset; shifting practices for learning and leading; fostering student voice and parent engagement. By committing to communities of practice, the network seeks to mobilize knowledge via four intersecting themes of social justice, inclusivity, safe acceptance, and cultural competency. Research themes discussed in the paper are: 1) school climate/culture as vital for success; 2) understanding systemic barriers and schooling as complex: bias, stigma, image, acceptance, resilience; 3) multiple supports for multiple school contexts; 4) what matters: community, caring teachers, student voice, parent engagement. This secondary school research and the larger research collaborative network follows suit, and adds further dimension to wide-ranging school communities as well as to its innovative reach in teacher education because it places, for the first time in Canadian poverty-school based research, student voice at its center.
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 | 0.095 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.029 | 0.040 |
| Scholarly communication | 0.025 | 0.023 |
| Open science | 0.004 | 0.025 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".