The political rhetoric of social problems: gasoline sniffing among the Innu of Labrador
Bibliographic record
Abstract
In 1993, six Innu youth from Davis Inlet were the focus of a home video that showed them high on gasoline fumes and shouting suicidal threats. The release of this video to media was undertaken by Innu representatives who claimed that they could not help their children and requested that the governments offer aid to treat these children and numerous others in the community. This 'crisis' changed the way in which negotiations took place between Innu and governments, as the gasoline sniffing home video was part of a political agenda of Innu leaders to embarrass the governments into taking action. Undertaking a social constructionist perspective and Critcher's natural history model, the gasoline sniffing crises of Labrador Innu communities of Davis Inlet and Sheshatshiu are examined to determine who was involved in bringing attention to this 'problem', what the political stakes were in their involvement as well as some of the intended and unintended consequences of this media spectacle.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.036 | 0.024 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".