Abnormal in Alberta: The Genealogy of “Severely Normal” as a Biopolitical Dog Whistle
Bibliographic record
Abstract
The phrase “severely normal” was often used by Premier Ralph Klein in 1990s’ Alberta to describe the Albertans he wished to interpellate, and it has had enduring power as a dog whistle by the political right in the province. Against commentators who see it as only a facile populist gesture, in this article the author deploys Foucault’s lectures on “racism against the abnormal,” together with Ladelle McWhorter’s interpretation, to argue that there is a historical and conceptual continuity to “severely normal” that ties back to Alberta’s infamous eugenic history. Articulating this genealogy enables the connection of political struggles on the part of sexual minorities, disabled people, members of non-normative families, and Indigenous people and illuminates the biopolitical rhetoric of successive Conservative governments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".