STRATEGIES IN INCULCATING UNITY VALUES AMONG HIGHER EDUCATION INSTITUTIONS STUDENTS
Bibliographic record
Abstract
Unity in a society is the backbone of a nation's productivity and harmony. Therefore, in order to keep the country in a peaceful state, unity among races must be nurtured and maintained. Therefore, this study was conducted to assess the strategy for enhancing the level of integration among (IPT) students. The methods of this study are quantitative research and the research question is to assess strategy for enhancing the level of integration among (IPT) students. This study was conducted through the dissemination of questionnaires and the sample consisted of local (IPT) students. A total of 1000 manuscripts were distributed and from that 478 manuscripts were returned and analyzed. This research found that most (IPT) students are on a medium level of understanding of the unity concept. In addition, this study found that these students lack the will to assimilate among them in totality which is the chief objective of the unity concept. Therefore, it is recommended that the cultivation of the spirit of unity must begin from as early as the family unit and also at the pre-school level. In addition, emphasis should also be given to the usage of the Malay language as the official language of unity and learning in the universities. It is also recommended that reforms must be made and that elements of national unity must be embedded in all university programs so that it will inculcate openness and acceptance among all citizens towards true national unity. This research was funded under the Ministry of Higher Education Fundamental Research Grant Scheme (FRGS).
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".