Out-migrants and Local Institutions: Case Study of a Depopulated Mountain Village in Japan
Bibliographic record
Abstract
Rural depopulation is now well acknowledged to be one of the salient challenges faced by Japan (Ohno, 2005; Odagiri, 2006). However, out-migrants that left their village of origin still maintain their bond with the villages through local institutions and natural resources. By taking Mogura village in Hayakawa town, Yamanashi prefecture as a case study, this article discusses relationships between out-migrants and their depopulated village of origin by focusing on local institutions and natural resource management. Data was collected using open ended interview and participant observation methods. The result shows that, although the style of observing has changed, out-migrants play important role in local institutions and assisting resource management of their depopulated village of origin. The institutions still have meaning for out-migrants to keep relationships with their village of origin. Several customs, such as collaborative labor, obon, New Year vacation, and the anniversary of ancestors’ death ceremony, provide scheduled opportunities for out-migrants and residents to get together and good reasons to come to the place of the village of origin. We argue that local institutions and natural resources, although in the process of transformation, can be helpful tools to link out-migrants with villages. We, however, take precaution on whether such role will be transferred to next generation of the out-migrants that are born and are living outside the village of origin of the out-migrants.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".