Adult education and the aesthetic turn: (Re)Imagining for a troubled world
Bibliographic record
Abstract
We live in a deeply troubled world of global patriarchal capitalism that has put lives in peril and made critical adult education work extremely challenging. Grounded in theories of the imagination and the need for a different imaginary, we explore the aesthetic turn in adult education, and specifically how artsbased and creative approaches are being mobilised by adult educators in Canada and across the globe to address social issues and (re)imagine who people are and what they are able to see, hear and know. We concentrate on varied examples of work with marginalised populations in diverse settings and institutions including communities, museums, libraries and universities. We explore how aesthetic practices reshape perception, disrupt silences, look back to think forward, dislodge fixities of commonsense, encourage cultural democracy and democratise culture. By exploring a diversity of practices and locations, we illustrate the range and scope of aesthetic pedagogical practices and emphases. While aesthetic educational work cannot change the world alone, we argue that it is upholding the critical social purpose of our field by encouraging new competencies of seeing, knowing, identifying, visualising, historicising and democratising in the interests of a just world for all.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.080 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".