Bibliographic record
Abstract
This chapter describes a new, highly gendered economy of boom and bust, haves and have-nots, in Canada's easternmost province, Newfoundland and Labrador. The province had long been the poor cousin of Confederation. By 2008 this all changed, as Newfoundland and Labrador became a “have province” due to the cyclical but steady rise in total oil production from the province's offshore oil wells. However, the oil boom could not transform overnight serious environmental, economic, and social problems that have been plaguing Newfoundland and Labrador since at least the 1970s. The limits of the boom are apparent from the experience of working people. Outside of the region surrounding St. John's, the provincial capital, skilled working people have continued to leave the province due to ongoing crises in the forestry and fisheries sectors. Direct employment in the oil and mining sectors is too limited to compensate. The oil boom has further contributed to a neoliberal policy of dividing unions, especially in the public sector.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.095 | 0.031 |
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".