Aboriginal Employment in the Alberta Oil Sands: Success and Barriers to Success
Bibliographic record
Abstract
As the baby boomer generation retires from the workforce, the current shortage of skilled workers is expected to increase dramatically. Alberta’s oil sands will experience those shortages intensely, especially as the Temporary Foreign Workers program, responsible for a significant amount of oil sands labour, reduces the number of available workers further still. As investment in oil sands development increases, so do the number of jobs, in contrast to a decreasing labour pool. Yet the Aboriginal population is both growing and younger than the non-Aboriginal population, and the time is right to increase Aboriginal representation in the workforce, for everyone’s benefit. The purpose of this paper is to identify differences in employment practices between successful Aboriginal employers and non-Aboriginal employers, and determine if those differences support successful employment or not. The methodology used was qualitative analysis based on a case study of Cold Lake First Nations. Although a small convenience sample, the data gathered provided a personal and honest, first-hand view, through an Aboriginal perspective. Data was gathered from various stakeholders, including energy companies, successful First Nations employers, First Nations workers and a First Nations employment and training agency. Analysis considered Aboriginal education and funding, Budget 2013 financial allocations to Aboriginal communities, employment sustainability within communities, and First Nations consultation and collaboration. Results found three significant differences in hiring practices between Aboriginal and non-Aboriginal employers which currently favor Aboriginal employers for the Aboriginal worker. Should energy companies wish to increase Aboriginal representation in their workforce, recognition of these differences is critical.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".