"I D O N T REALLY LIKE THE MILL; IN FACT, I HATE THE MILL": Changing Youth Vocationalism Under Fordism and Post-Fordism in Powell River, British Columbia
Bibliographic record
Abstract
FOREST TOWNS IN BRITISH COLUMBIA are in the throes of. a profound restructuring (Hayter 2000). The most recent turn of the screw, the US imposition of a 27 % import tax on softwood lumber (May 2002), is only the latest twist in a twenty-year history scarred by volatility and industrial downsizing. Persistent job losses due to technological change, corporate rationalization, increased international competition, trade conflicts, and resource deplet ion have progressively undone the fabric of BC forest communities, especially on the coast. But while a plethora of policies, schemes, and programs have been initiated to help those worst affected, little attention has been paid to high school youth who have yet to enter the job market (Hay 1993; Barnes and Hayter 1992,1995a,
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".