Over-qualification in the Workforce: Do Indigenous Women and Men Benefit Equally from High Levels of Education?
Bibliographic record
Abstract
Using data from the 2016 Census, this study examined the level of education–job mismatch (over-qualification, in particular) in the Canadian labour market among Indigenous women workers aged 25 to 64 who received post-secondary education. Their rate of over-qualification was compared with that of Indigenous men as well as non-Indigenous workers. In doing so, this study aimed to shed some light on the effect of post-secondary education on labour market outcomes by investigating whether Indigenous men and women benefit equally from their post-secondary education. Compared to their non-Indigenous counterparts and Indigenous men, Indigenous women workers with university-level education (bachelor’s degree or higher) were less likely to be over-qualified. Conversely, Indigenous women workers with post-secondary education lower than university level were more likely than non-Indigenous women and Indigenous men to be over-qualified. This pattern persisted after sociodemographic factors were controlled for. The results suggest that, among those with a post-secondary education, higher levels of education were especially advantageous to Indigenous women.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".