CHAPTER 7 Issues of Disparity, Distribution, and Economic Dependency in Northern Ontario
Bibliographic record
Abstract
T his chapter discusses some key features of employment condi- tions and income distribution in Northern Ontario in light of the region's long-term decline in population and employment.To begin, the colonial structure of Northern Ontario continues to be reproduced in the reserve system and in other colonial-racial disparities.As Table 7.1 indicates, the 2016 census counted about 125,000 persons with Aboriginal identity, or 17.3% of the Northern Ontario population.Even using fawed ofcial labour force statistics, several measures show the colonial-racial gap between non-Indigenous persons and Indigenous persons, both on and of reserve.While Indigenous-identifed persons made up 17.3% of the population and 15.2% of the working-age population (15 years of age and over), they comprised 13.6% of the employed population and 25.7% of unemployed t 1 n O .0 9 5 8 9 2 9 2 3 9 Indig.6. 0. 4. .8. ..0 .
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".