MANAGEMENT OF CROATIAN PUBLIC HIGHER EDUCATION INSTITUTIONS BASED ON PERFORMANCE MEASUREMENT
Bibliographic record
Abstract
To responsibly manage higher education institutions' business, public managers need to dispose of budget funds rationally. Responsible management needs to have quality and timely information based on measuring and monitoring performance. This paper has two main aims. The first aim is to analyze the importance of measuring higher education performance in general and provide an overview of higher education performance indicators in selected countries. Through literature review, we analyzed performance measurement in higher education of Australia, Canada, the UK, the Netherlands, Finland, Romania, and Poland. Through a review of the literature, it is concluded that performance measurement exists in higher education and is used for management purposes in the observed countries. The second aim is to investigate whether the management of the public higher education institutions in Croatia is based on performance measurement results. To meet this goal, an empirical study was conducted. Research conducted in the Croatian public higher education has also shown a certain level of awareness of the need to measure performance and use measurement results in management processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".