Teacher Voice in Saskatchewan
Bibliographic record
Abstract
Teacher voice, defined as a meaningful inclusion of teachers or their union in decision-making in school systems, provides a perspective on educational policy that is not often utilized in policy research (Diem et al., 2019). However, teacher voice can illuminate insights on policy in the classroom. This study aims to investigate the inclusion or exclusion of teacher voice in a specific policy, the Education Sector Strategic Plan 2014 – 2020 in Saskatchewan, and then determine if their perceptions of inclusion affected the implementation of the policy in the classroom. As a secondary research area, the research attempts to discover if neoliberalism influenced teachers' involvement in decision-making. Critical discourse analysis was used to inspect relevant documents and interview transcripts within a critical policy structure that separated policy into three stages: development, delivery, and implementation. Policy delivery is the preparations for implementing policy such as professional development. Teacher voice was found not to be included at any stage of the policy and there were indications of neoliberalism in the documents and transcripts. Teacher participants described increased time required for the assessments under the policy and felt the consequences of a managerial structure of decision-making. Both of these neoliberal elements limited teachers’ professional judgement and opportunities for voice. The research can be useful for teacher unions and partners in education desiring to make policy more inclusionary.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".