A CASE OF TEACHER OPPOSITION TO SCHOOL DISTRICT ASSESSMENT AND EVALUATION POLICY
Bibliographic record
Abstract
Better School District introduced its assessment and evaluation policy and regulations in 2006. Three years later, the Director of Education learned that the policy was not fully implemented in all schools. The main issue was teacher noncompliance with the provision of interventions for students who miss assignments and tests or submit work late. Principals were aware of this issue in their schools yet did not address it. In 2010, the district commenced a review of the policy and developed regulations to support it. When released in 2011, the revised policy met with opposition. This case focuses on the district’s process for policy development, teacher engagement in policy development, and the role of principals and other leaders in implementing change.
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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 | 0.042 | 0.092 |
| Meta-epidemiology (narrow) | 0.000 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.032 | 0.016 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.019 | 0.026 |
| 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".