Apprentissage non formel dans quatre espaces créatifs québécois : analyse basée sur la théorie de l’activité
Bibliographic record
Abstract
Creative spaces allow users to craft, transform and equip themselves, as well as participate, share and learn. These actions support the democratization effect of the maker movement (Hatch, 2014) as well as the development of the empowerment made possible in creative spaces (Blikstein, 2013; Davidson and Duponsel, 2021). This article presents the analysis of four creative spaces in Quebec and leads to identify the characteristics of learning spaces located outside educational institutions and supporting non-formal learning. The view on creative spaces has been guided by activity theory (Engeström, 1987). Different components (subject, tool, object, division of labor, rules and community) were analyzed through transcripts of semi-structured interviews conducted with managers of creative spaces and users. The analysis supported by activity theory makes it possible to approach in a systemic way the organization of activities in creative spaces that support non-formal learning. Our project is of interest for the advancement of knowledge, because it allows us to identify tensions related to notoriety, equipment, learning and community that could be present in other creative spaces.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".