The Development of the Assessment Methods of the Organizational Potential of the Institutions of High Education
Bibliographic record
Abstract
In strategic documents of the Russian Federation the development of education is considered as one of the objectives of socio-economic development of the country. Nowadays, despite the considerable interest of the scientific community to the problem of the effectiveness of higher education institutions, there are no scientific studies to enable a comprehensive approach to the assessment of the organizational capacity of universities. The purpose of this article is to solve the most important managerial task through the development of a methodology for assessing the institutional capacity of higher education institutions. The article contains a critical analysis of the approaches to the assessment of the effectiveness carried out in practice in the institutions of higher education.It was settled that organizational potential is the basic element of the mechanism, which enables to enhance the operating benefits of institutions of high education. The author’s approach to the organizational potential structuring of the university is suggested. The organizational potential assessment method enables to take into account the cumulative effect of many factors on the operating benefits of the university management. The functioning of the proposed methods in the managerial practice will favour accumulation of the organizational potential of the universities and improve the efficiency of their work. The study developed the methods with the following characteristics: firstly, it provides the possibility of considering the institution of high education as a subject of market relations and the use of many factors that can be later supplemented in calculation; secondly, there is a possibility to take into account territorial characteristics of the regions in which universities operate when calculating the effectiveness of universities; thirdly, the technique allows not only to determine the level of private indicators characterizing the efficiency of organizational potential, but also to identify existing reserves of development, to identify key factors that have the greatest impact on the effectiveness of the university activities, united on a territorial basis, and to compare the objects of study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".