University and community partnerships in South Sulawesi, Indonesia: Enhancing community capacity and promoting democratic governance
Bibliographic record
Abstract
South Sulawesi is a province in Indonesia where the majority of the population is Muslim, with many variant interpretations of Islam. Alauddin State Islamic University is not just a place for teaching and study but also plays a role in helping to unify the differences among these different Islamic groups. Its changing of status from institute to university in 2005, and later the support of the Canadian-assisted SILE Project beginning in 2010, have made this university an example of reform in the way it implements its functions. Since 2011, Alauddin State Islamic University has been developing a new approach in university-community outreach/engagement. What was formerly separated between teaching, research and community service is now linked under one institutional umbrella. The new university-community outreach approach has also adopted some new tools like Asset Based Community Development (ABCD) and Results Based Management (RBM). It seeks to promote democratic governance, gender equality and a sustainable environment. The university also works in partnership with civil society organisations (CSOs) in South Sulawesi, including Islamic-based organizsations, secular organisations and women’s organisations. The model for the partnership is a working group (abbreviated to pokja in Indonesian), which comprises lecturers from a faculty in the university and members of a CSO. We discuss the opportunities and challenges faced by these working groups. Opportunities include increased advantages from pooling their organisational capacities and experience in working with communities. Sharing their networks and resources makes them stronger and makes their work more sustainable. The challenge lies in changing the mindset from a needs-based, project-oriented approach to an asset-based facilitative approach, comprehending the tools, managing time to work together and building effective teamwork. Keywords: university-community outreach, democratic governance, asset-based community development, opportunities and challenges
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| 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".