Early stages in building hybrid activity between school and work: the case of PénArt
Bibliographic record
Abstract
This formative intervention documents the emergence of a hybrid activity aiming at student engagement and academic achievement. In this context-bound study, early stages of this activity consisted in establishing PénArt meant to enable high school students with difficulties to start up their own business at school. It involved reaching agreements between a high school and a youth centre so that high school students engage in the production and selling of their branded t-shirt. At the frontiers of their respective activity system, students, youth workers, special education teachers and members of the school board took actions to cross boundaries and redefine their interrelations. Cultural historical activity theory was fruitful to document the development of a new object-oriented activity. Tensions and contradictions revelaled to be the key moments in the emergence of the hybrid activity. Expansive learning led us to understand that, in a conflicting situation, a collective’s agentive actions create an expansive form of learning and leads to a successful entrepreneurship experience. Change laboratory capacity to foster change for cooperative education in Quebec was successful. The students enrolled in a regional entrepreneurship contest and won it. That was a significant event for students with low self-esteem linked with their performance at school.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.014 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".