Islam, Democracy and University-Community Engagement in Indonesia: learning experiences the State Institute of Islamic Studies IAIN Sunan Ampel Surabaya Indonesia
Bibliographic record
Abstract
Experiences the State Institute of Islamic Studies IAIN Sunan Ampel Surabaya Indonesia This session is intended to share the experience, challenges and potential of IAIN Sunan Ampel, a public Islamic higher educational institution in Surabaya, Indonesia. Indonesia, as the world’s most populous Muslim nation has long been known for its moderate approach to Islam. IAIN’s historic focus has been on teaching and teacher training, in support of an extensive network of Islamic boarding schools (pesantren and madrasah). In the last ten years, it has started to engage in organized community outreach through its KKN (Students engagement in community) program which uses a Participatory Action Research approach. Recently IAIN has been challenged to expand its approach to community engagement by two important initatives. The first is IAIN’s transition from Institute to University which will expand the current academic programs by adding natural sciences, social sciences and humanities and thus opening academic studies in areas non-Islamic such as Public Health, Engineering, Politics, Economics and Social Work. This will expand the scope of IAIN engagement programs from its historically religious focus into a range of broader issues important to the development of democracy in Indonesia, such as conflict resolution, development, poverty and social welfare. At the same time a new national law (No. 12/2012) on Higher Education has come into effect, emphasizing the significance of University community outreach. This is a very important factor since one of the barriers to community outreach development in IAIN has been the absence of strong supporting regulations. Through its involvement in a jointly funded Canada-Indonesia project on university-community engagement, IAIN is working in partnership with a range of community organizations to develop new forms and approaches to community engagement and to integrate the work of its community partnerships into curriculum, research, and community services.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".