Teachers’ Codes of Ethics: A Priority? Or a Consequence of Government/Union Relationships, Ideology, and Legislation?
Bibliographic record
Abstract
In this paper, I share findings from a historical investigation into how the Saskatchewan Teachers’ Federation’s (STF) Code of Ethics has evolved as a direct result of changing legislation. This study was based on the idea that codes of ethics are not stand-alone documents created by professional organizations to guide ethical behaviour, but policies that are a direct reflection of the relationship the profession has with the government in power. I demonstrate that the initial creation and all subsequent revisions of the STF Code of Ethics have never been independent of legislative changes. Rather, changes to the ethical code have been reactionary to political activity and dependent on the legislated changes made by the government in power.
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.050 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".