Bibliographic record
Abstract
This article traces the principles underlying the development and implementation of a graduate interdisciplinary course on socially engaged art.We undertook this course as a collaborative effort between our disciplines of social work and image arts.As educators who have a passion for social change and the arts, we sought to introduce students to methods and theories of engaging communities through collaborative artistic practices.In this article, we pause to reflect on our experiences designing and coteaching the course over two years beginning with a discussion of the intentional pedagogy that guided the development of the course including an emphasis on experiential, active and peer learning.We illustrate these principles through concrete examples in course design including assessment methods that valued and promoted building classroom interaction and relationship-building.We also highlight two specific student case examples demonstrating issues related to engaging communities.The article ends with our reflections on own learning in the course and how this relates to principles of student engagement.
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 | 0.006 | 0.012 |
| 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 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.043 | 0.007 |
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".