Knowledge Management Strategies for Organizational Management of Higher Vocational Education Administrators in Liaoning Province, China
Bibliographic record
Abstract
The objectives of this research were: 1) to study the current situation and knowledge management strategies for organizational management of higher vocational education administrators in Liaoning province, China, and 2) to provide knowledge management strategies for improving organizational management of higher vocational education administrators in Liaoning province, China. 3) to evaluate the adaptability and feasibility of knowledge management strategies for improving the organizational management of higher vocational education administrators in Liaoning Province, China. The sample group for this research was 205 administrators from 10 vocational universities in Liaoning by simple random sampling. The interview group was 10 high-level administrators, and five experts evaluated the adaptability and feasibility of higher vocational education administrators' knowledge management strategies and organizational management. The research Instruments include 1) a questionnaire, 2) a structured interview, and 3) an evaluation form. Data analyses were frequency, percentage, mean, standard deviation, and content analysis.The results showed that 1) the current situation of knowledge management strategies for organizational management of higher vocational educational administrators is divided into three aspects: management effectiveness, knowledge management, and organizational culture; and 2) the knowledge management strategies for improving organizational management are divided into three aspects as follows: 12 measures for knowledge management, 11 measures for organizational culture, and 10 measures for management effectiveness. 3) The results of evaluating the adaptability and feasibility of the knowledge management strategies for improving organizational management were at the highest level.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".