Development of Smart Human Resource Planning System within Rajabhat University
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
The purposes of this study were to 1) develop of Smart Human Resource Planning System within Rajabhat Universities and 2) study the results of official performance evaluations of academic staff with Smart Human Resource Planning System within Rajabhat Universities. The samples included 8 system development experts via purposive sampling and 94 academic staff by multi-stage sampling. The research tools composed of 1) performance assessment form using 5-point Likert scale for Smart Human Resource Planning within Rajabhat Universities and 2) performance evaluation form for academic staff with Smart Human Resource Planning System within Rajabhat University. The research observations were concluded into 2 ways. First, the Smart Human Resource Planning System within Rajabhat Universities development has overall performance at the high level. For instance, the efficiency of all Modula test was displayed at the high level. In addition, both System test, Usability test and Security test were shown at high level as well. Second, the response of performance evaluation form through academic staff using Smart Human Resource Planning System was all exhibited at high level. However, “The people involved with the system” assessment list with in performance evaluation form was indicated at highest level.
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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) | 0.001 | 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 it