Oil and gas and the Inuvialuit people of the Western Arctic
Bibliographic record
Abstract
Purpose To learn how Inuvialuit people feel about the oil and gas activities on their land. Design/methodology/approach Interviews were administered to a stratified sample, on Inuvialuit land. Participants included: Inuvialuit elders; entrepreneurs; public servants; employees of the private sector; managers of oil companies; unemployed persons; housewives; the mayor of Inuvik; and the first aboriginal woman leader in Canada. Findings It was reported that oil and gas industry activities are having a positive impact on the regional economy, creating indirect as well as direct financial benefits for the Inuvialuit among others. However, some residents qualified their support saying that they are in favour of continued activity only if benefits filter to them as opposed to being enjoyed only by oil companies and migrant employees. Concern was also expressed for the environment and for the threat that development brings to wildlife upon which people rely on as a food source. Research limitations/implications This study should have a longitudinal follow‐up. Practical implications While oil and gas exploration and the building of a pipeline may have economic advantages, this might have social, cultural and environment costs for the Inuvialuit. Originality/value The paper illustrates how oil and gas activities on Inuvialuit land will transform the lives of these people.
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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 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".