Constructing the Model of Aboriginal Tribal Social Enterprises from the Concept of Social Economic Enterprises
Bibliographic record
Abstract
Taiwan's aboriginal tribes have long been affected by political forces and market economy model, and the aboriginal people living in remote mountainous areas with lack of information have met with a lot of economic and social problems and challenges such as loss of land and traditional culture, aging population and stagnation of tribal industry development. Therefore, the original self-sufficient tribes began to prone to “poverty”, and this is one of the most critical social issues for Taiwan to cope with. The purpose of this paper is to discuss the concept of "social economy" in the aboriginal tribes, to develop and restore the sharing economic cooperation model, to increase collective interests and to set up tribal social enterprises, so as to address the crucial social issues.This study will adopt the method and experience of socio-economic analysis to study the action plan of Seediq, a division of Taiwanese aboriginals, and their experience of social and economic organization and operation, and reflection on the social enterprise system. The main research is to explore the social economy in the Meixi tribe, the status quo and future development, and how to employ social innovation to promote the tribal social enterprise planning and business model.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| 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".