Management of Higher Education Institutions as a New Tool for the Development of Higher Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Higher education is extremely important for the socio-economic development and cultural enrichment of society, providing people with the relevant knowledge and skills to improve their skills and productivity in the context of further global development. Today, the task of effective resource provision and high-quality organization of the student learning process is extremely relevant in the world. The formation of a new mentality of all stakeholders in the educational process in a rapidly changing information environment is of great importance. This task requires constant monitoring and evaluation of the education system based on the collection, processing, and analysis of data necessary to make informed management decisions for the optimal development of higher education. The article aims to highlight the main patterns of management of higher education institutions with a view to their development reflected in the scientific literature, and to clarify certain practical characteristics of this process. In the process of preparing this study, the analytical and bibliographic methods, induction, deduction, and analysis were applied. The synthesis of information was used to study the scientific literature on issues related to the management of HEIs. Meanwhile, systemic-structural, comparative, logical, and linguistic methods, abstraction, and idealization were applied to study and process data. Among other things, the authors of the study conducted an online questionnaire survey to clarify certain aspects of this issue practically. Based on the results of the study, the theoretical aspects of the use of management tools as a tool for the development of HEIs have been studied. Moreover, some practical issues related to the management process in higher education have been characterized.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it