Aboriginal/Non-Aboriginal Wage Gaps in Canada: Evidence from the 2011 National Household Survey
Bibliographic record
Abstract
The fact that Aboriginal peoples in Canada have experienced sizable and persistent earnings disadvantages is well documented. However, the most recent estimates of Aboriginal-non-Aboriginal wage differentials utilize data from the 2006 Census . The present analysis seeks to address this gap by providing more recent estimates of Aboriginal earnings disparities for various groups of full-time, full-year workers using data from the 2011 National Household Survey (NHS). We estimate and decompose Aboriginal/non-Aboriginal wage gaps at the mean for a number of different Aboriginal and non-Aboriginal groups living on- and off- reserve. We find that, consistent with previous literature, Aboriginal peoples continue to experience sizable earnings disparities relative to their non-Aboriginal counterparts. We find that Aboriginal Identity respondents living on-reserve experience the largest earnings disparity, followed by males who identify as First Nations and live off-reserve. Respondents who report Aboriginal ancestry, but who do not identify as Aboriginal persons, experience the smallest earnings disadvantage. Results of the decomposition analysis reveal that, unsurprisingly, educational attainment is the most salient factor contributing to the explained portion of the earnings disparity between Aboriginal and non-Aboriginal Canadians. Somewhat disconcerting, we find that where wage disparities are the largest, the explained proportion of the gap tends to be the smallest. Although previous studies can only serve as a rough comparator, relative to earlier estimates of Aboriginal/non-Aboriginal wage differentials using previous census periods, we find that earnings disparities among Aboriginal ancestry groups have remained relatively constant; wage gaps for Aboriginal identity groups have narrowed slightly; while the earnings disadvantage has widened for Aboriginal identity persons living on-reserve. Research and policy programs aimed at improving educational attainment and access to employment among Indigenous peoples are likely worthwhile initiatives. However, more research is needed on the potential role of discrimination in contributing to the persistent earnings disparities between Indigenous and non-Indigenous persons in Canada.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".