Dialogues of dominance: \nnarrative, occupational folklore, & the bullying of public-school teachers
Bibliographic record
Abstract
This thesis focuses on how childlore, narrative, and occupational folklore serve as the basis for how we view and respect teachers. Folklore is argued as both a cause of and a solution to the bullying of public-school teachers in Newfoundland, Canada. This thesis analyzes the language surrounding bullying, the close relationship between bullying and folklore (especially in regard to Folklore and Education, Occupational Folklore, and narrative study); instances that depict how this plays out in the lives of teachers, and finally, the methods that have historically been used to curb this in the past and how these ideas can be adapted and revitalized in the sphere of modern education. \nA note on capitalization: When referencing specific sub-disciplines, such as Folklore and Education or Childlore, I have capitalized the words in order to differentiate from references to general genres and examples, which are given as lower case.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.033 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 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".