Just Before you Close the Book on Keegstra ... Does he Exist in Every Classroom?
Bibliographic record
Abstract
All teachers have emotions, indeed passions. However, a common assumption is that the biases of a teacher are left at the classroom door as he or she dons the mantle of neutrality. The realistic nature of this assumption bears investigation. The Keegstra case illustrates the potential impact of the role of teacher and, in this regard, rural Alberta is no different from the rest of Canada. It is vital to consider some of the factors which enabled such teaching to continue for so long. The issue here is how the power of the teacher's role can be abused with less attention, the extent to which reasoning processes in classroom investigations are sought, and the extent to which the authority figures of our children allow or encourage challenge. Far more work is required concerning how values can be handled in a classroom if such dogmatic teaching is to be prevented, and students are to be better equipped to deal with dogma when it does occur. The potential of such dogmatism must be acknowledged since to ignore it will not make it go away.
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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 | 0.000 | 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 | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.089 | 0.029 |
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".