Bibliographic record
Abstract
Partnerships between schools and community arts organizations offer the opportunity to strengthen the teaching and learning of dance, drama, music and visual arts in Canadian classrooms. This presentation will recount the findings from in-depth interviews conducted with 53 participants (artists, teachers and project coordinators) in 14 sites across Canada and 3 parent volunteers. Based on the interview findings, an ideal collaborative program would be characterized by the following elements: artists would be chosen based on the requirements of the project and the school; there would be team building workshops for the staff and artist before the project to develop collaborative skills; adequate time for planning, implementing and debriefing would be provided; important decisions, such as purpose, theme, scope, medium and student selection, would be made in the preplanning stages of the project; and finally, the schedule of the artists visits would correspond to the level of intensity of the project; for example, the artist could visit a school bimonthly at the beginning of the project and increase frequency of the visits as the project progresses and more artistic expertise is required.
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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.054 | 0.012 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".