The Role of Intermediary Organizations in Supporting Rural Arts Education
Bibliographic record
Abstract
Across Canada, the arts have emerged as a key strategy for revitalizing and sustaining rural communities, namely by developing the creative sector and nurturing the wellbeing of community members. Supporting youth mental health and creative skill-building through arts education is particularly critical, in this sense, as the vitality of rural communities depends significantly on retaining a thriving youth population. Access to arts education for youth, however, is not consistent across Canada, particularly in the realm of school-based arts education. This issue is exacerbated in rural and remote communities experiencing additional barriers, such as the costs and distance involved with going on field trips, ordering art materials, and offering teacher professional development in thearts. In these circumstances, rural schools might seek out the help of a third-party intermediary organization to facilitate partnerships with artists, funding bodies, and other entities to support arts education. In this presentation, I will present key findings from my doctoral research that illustrate how intermediary organizations support rural schools by a) identifying existing community assets to support the growth of arts education and b) offering key resources, guidance, and partnership facilitation to assist them in developing arts education initiatives.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".