Bibliographic record
Abstract
AbstrACt this article introduces a political-economic framework for analyzing young peo-ple’s production of user-generated content (UGC) as a kind of apprenticeship labour. based on case studies of four young Montréalers engaged in creating user-generated content, the au-thor developed the apprenticeship-type model of UGC labour to denote a process by which on-line immaterial labour or “free labour ” coincides with self-directed and informal job training, channelled specifically toward a career in the creative industries. the 20- to 24-year-old par-ticipants ’ online activity is seen as a non-remunerated training ground, driven by the promise of notoriety that begets autonomous future employment in areas such as fashion, music, and journalism. throughout this process, young people must constantly negotiate their autonomy; negotiated autonomy is precisely what they are apprenticing into through UGC production, where uncertainty and flexibility serve as the hallmarks of new media working conditions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".