Employment Patterns 2009–2010 In Canada: A Dark Cloud for Aboriginals with a Silver Lining
Bibliographic record
Abstract
The Canadian economy grew in 2010, compared with 2009 and employment rates increased marginally. However, the picture is different for Canadian Aboriginal peoples living off reserve, as they experienced a decline. Data is unavailable for those living on reserves. The decline in employment levels was the case for both men and women in all age categories, except for women from 15 to 24. There was also a decline in Aboriginal employment rates in seven of the ten provinces. In contrast the three territories experienced an increase. In 2010 Aboriginals had a lower employment rate than non-Aboriginals in all ten provinces and the three territories and in every age group, except for women over 55. However, a meaningfully different picture appears when employment rates are examined by educational level. The higher the educational level the higher the employment level. This applies to both Aboriginals and non-Aboriginals. Further, there is only a minimal difference in employment levels between Aboriginals and non-Aboriginals, when examined by their educational level. One conclusion is that education appears to be a path for greater employment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".