Fighting Firewater Fictions: Moving Beyond the Disease Model of Alcoholism in First Nations
Bibliographic record
Abstract
In Fighting Firewater Fictions, Richard W. Thatcher describes and explains the emergence and perpetuation of the 'firewater complex' – the cultural construct of an informally sanctioned, destructive, binge-drinking norm in First Nations reserve communities.The complex has reified alcoholism as an inevitability in the First Nations – an approach that has resulted in essential aspects of collective and personal responsibility being vacated in favour of therapeutic interventions assisted by social personnel of questionable expertise. This substitution has had the effect of relieving government policy-makers and reserve leadership from accountability for problematic community development strategies that have long since outgrown their support capacities.Thatcher argues that the conditions that give rise to extraordinary alcohol abuse rates in First Nations are largely traceable to the hopelessness associated with multi-generational unemployment. Fighting Firewater Fictions calls for community re-organization around a band development policy that looks beyond the reserve, and outlines a strategy that shifts the current, exclusive emphasis on the needs of alcoholics towards the neglected counselling and non-residential service needs of potential or actual binge-drinkers. This is essential reading for anybody working in, or seeking to understand, aboriginal communities that are experiencing problems with alcoholism
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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 | 0.000 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".