Adaptive Cycle Of The Wotsogo Village Community In Facing Covid-19 Pandemic In 2020
Bibliographic record
Abstract
COVID-19 is non-natural disaster that influenced in various sector of life, not only health, but also social-economic conditions, including Wotsogo Village. Therefore, it is important to conduct research related to adaptive cycle of Wotsogo Village community in facing of COVID-19. This adaptive cycle can reflect the level of community resilience which influenced by various factors. This research used descriptive qualitative method with Miles and Huberman's interactive model and scoring technique analysis. The results of the analysis show that adaptive cycle of Wotsogo Village community in facing of COVID-19 was marked by three moments distribution, were the first distribution moment of COVID-19 in Indonesia, the second moment is implementation of COVID-19 policies, and last the towards New Normal moment. The scoring results show that the level of resilience of the Wotsogo Village community was classified as moderate that spread in three RW areas and high that spread in nine RW areas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".