Antecedents of teachers fostering effort within two different management regimes: an assessment-based accountability regime and regime without external pressure on results
Bibliographic record
Abstract
This article focuses on comparison of antecedents of school teaching intensity exerted by teachers in two quite different accountability regimes: one management regime with an external-accountability system and one regime with no external accountability devices. The methodology involved was cross-sectional surveys from two different management systems: (1) teachers working under assessment-based accountability in a city authority (N=236) and (2) folk-high-school teachers who work without tests and examinations and thereby without external pressure on results (N=366). The purpose of the study was to estimate the path coefficients in structural equation modelling in the two regimes and compare the strength of relationships between concepts in the structural models. Through this comparison we draw inferences suggesting how the strength of accountability repercussions and other leadership antecedents can influence teacher learning intensity in teaching and how strength in qualitative aspects among school professionals may influence learning intensity in teaching. Implications for practice and directions for future research are discussed.
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".