Strategies of Sustainable Cooperative Partnerships
Bibliographic record
Abstract
Cooperatives also have an active role in efforts to enhance the life of the nation and to realize a national economy based on the principles of family and economic democracy. The problem faced by cooperatives today is that cooperatives are less able to become business institutions that provide good services to all members and society in general. Limited funds and low human resources become a barrier for cooperatives to develop. Partnerships between cooperatives and other financial institutions are alternatives to improve cooperatives in developing their businesses. This study purpose on developing a cooperative economic development through a strategic partnership approach between cooperatives and other financial institutions so that cooperatives can grow, develop, and be sustainable. The method used in this research is descriptive qualitative research using in depth interview with informant. The informant is a cooperative for savings and loan managers who are willing to be interviewed in Batu City. The results showed that the cooperative strategy in building partnerships between cooperatives and other financial institutions was carried out based on the principle of mutual benefit. Cooperatives need to improve themselves so that they can meet the feasible and bankable criteria. Thus partnerships between cooperatives and other financial institutions will be established, thus cooperatives will grow and develop.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".