Resource Dependence and Community Well‐Being in Rural Canada*
Bibliographic record
Abstract
Abstract The well‐being of residents of resource dependent communities is a question of traditional interest to rural sociologists. The label “resource dependent” obscures how this relationship may vary between particular resource industries, regions, or indicators of well‐being. Few analyses have compared the relationship between well‐being and resource dependence across different industries, nor tested competing theories about the relationship between resource dependence and well‐being. Our paper presents an overview of the relationship between resource dependence—agriculture, fisheries, mining, energy, forestry—and human well‐being in Canada. Analysis of 1996 Statistics Canada data revealed a great deal of variation in the effect of “resource” dependence on indicators of well‐being (e.g., human capital, unemployment, income): some industries exhibit fairly positive outcomes (e.g., agriculture), others more negative outcomes (e.g., fishing). Consistent with analyses conducted in the United States, these relationships vary by region, suggesting the need for models that incorporate the particulars of place and industry.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".