Kalosara Revitalization as an Ethno-Pedagogical Media in the Development of Character of Junior High School Students
Bibliographic record
Abstract
The aims of the research are (1) to identify types of character through kalosara revitalization as an ethno-pedagogical media in social sciences (IPS) learning at junior high school (SMP), (2) to develop strategy of kalosara revitalization as an ethno-pedagogical media in the development of characters of students, and (3) to develop a model of student character education through kalosara revitalization in IPS learning in SMP as an ethno-pedagogical media. The research is conducted through naturalistic approach. The research subjects are social science teachers at the junior high school, junior high school principals, and local public figures. Data collection is conducted at SMP Negeri 1 Wawotobi representing a heterogenous student group. Data was collected qualitatively using domain and taxonomy analysis models. Research result indicates that: (a) there are 74 values identified and distributed in 18 types of character that can be developed through kalosara revitalization as an ethno-pedagogical media in social sciences learning in junior high school, (b) kalosara revitalization strategy, as an ethno-pedagogical media in the development of characters, is conducted in form of integration in each theme and sub-theme in the syllabus of social sciences subject, (c) The character education development model through kalosara values as an ethno-pedagogical media indicates that there are three strengths of the model, i.e.: it elevates the local culture into national culture, it is a scientific model, and it is easy to understand and implement by teachers and students.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".