Process of Local Wisdom Transfer to Promote Good Relationship between the Elderly and New Generations
Bibliographic record
Abstract
Thai society is undergoing conflicts in the relationship between new generations and the elderly caused of the different frameworks of beliefs. The wisdom transfer process, an approach used in old times, is a solution to such conflicts. However, currently, it is used as a support mechanism. This research aims to develop a wisdom transfer process to ensure a good relationship between new generations and the elderly and study its efficacy. The process was applied to the elderly and new generations in Thung Samo Community, Phanom Thuan District, Kanchanaburi Province. The wisdom transfer process consists of 5 steps, namely Step 1: Agreement of local wisdom learning between the elderly and new generations, Step 2: Learning the background of local wisdom, Step 3: Learning by doing, Step 4: Local wisdom creation based on the ideas of young generations, and Step 5: Publicising the learned local wisdom achievements could boost the relationship between the two age groups, with a higher mean in the post-process. More outstanding communication between the two age groups was the key to better understanding between new generations and the elderly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".