THE CONCEPTS OF QUALITY AND ACCOUNTABILITY IN GENERAL AND HIGHER EDUCATION
Bibliographic record
Abstract
This article presents three measures of educational quality and six types of accountability, noting that these terms are complex and often contradictory. These terms are often used uncritically, with the result that educational policies following from them are misconceived or simply drift. For educational policies to be sound, they must be based on a clear use of terms and on a sound understanding of desired objectives. These objectives are matters both of stakeholders’ preferences and politics. The subjective and political nature of educational policies should be recognized, so that there can be formed an explicit basis for and consensus around appropriate educational objectives. The purpose of this article is to bring clarity to the common concepts of quality and accountability in education, so that educational policies may be better informed. The methodological basis of the research is the methods of comparative analysis of scientific research in the field of social and natural sciences, the authors of which investigated human, social and cultural capital. The educational establishments of all countries need from time to time to deeply re-examine certain operative concepts. In this regard, an informed consensus needs to be reached about the multidimensional and sometimes contradictory notions of quality and accountability. Habit and drift are not helpful to educational policy; instead, educational values and goals should be actively discussed and clarified in broad national discussions, comprising all major interested parties. A good educational system is ultimately a civic achievement, set within a community of informed and interested stakeholders.
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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 | 0.023 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".