Learning what you cannot say: public school teachers and free speech, an exploratory qualitative study
Bibliographic record
Abstract
This thesis examines the impact of teacher perceptions of free speech on teacher identity and school cultures. Based on interviews with twenty-two teachers in Newfoundland and Labrador, the research explores how perceptions of free speech influence teachers' understanding and performance of their professional identities. Results suggest that teachers are uncertain about the nature and meaning of free speech and that this has a detrimental impact on teaching and learning as well as their ability to participate in school governance initiatives. -- Informed by critical, democratic theories of education, the study explores demands faced by teachers as employees who are also professionals. Participants described a type of professionalism that was rooted in service, obedience and compliance and, which, along with the notion of the reasonable limitation, acted as a disciplinary norm. Significantly, when talking about free speech most teachers emphasized the importance of learning what one cannot say. More specifically, many teachers commenced their exploration of the concept of free speech by focusing on the notion of a reasonable limitation rather than considering the nature and existence of any right. Teachers treated free speech in the workplace as more of a privilege than a right and expressed great reluctance about speaking critically in the public sphere where their views could contribute to an informed public dialogue about contemporary educational issues. -- Free speech, participants suggest, rather than being speech without limits, is the ability to express oneself with minimal administrative interference and often within the context of a "troubled agency". The latter results when teachers are forced to contest professional identities in school systems whose objectives are sometimes at odds with the best interests of students. Between the poles of speech and silence a broad range of speech practices and conceptions of free speech exist. Collectively, these findings suggest a need for further research as well as a renewed emphasis on the democratic role of public schooling within professional associations, teacher-education programs and schools themselves. \n
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.019 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".