Bibliographic record
Abstract
This article introduces a political-economic framework for analyzing young people’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 author developed the apprenticeship-type model of UGC labour to denote a process by which online 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 participants’ 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".