“If Somebody Needed Help, I Went Over”: Social Capital and Therapeutic Communities of Older Adult Farmers in British Columbia Floods
Bibliographic record
Abstract
Abstract Older adults in disaster contexts are often thought of as a passive, vulnerable population that lacks agency and capacities to cope in the aftermath. However, it can be argued that older adults may have underrecognized strengths that can be utilized pre-, peri-, and post-disaster. One of these strengths is older adults’ unique social capital that stems from long-standing connections with other members of their respective communities. Using data from in-depth, semistructured interviews with farmers in British Columbia 3–11 months after the 2021 floods, this research explored the experiences of older adult farmers’ recovery. The farmers discussed how they leveraged their social capital to aid in their recovery efforts from the flood event. By using their bonding social capital, older adult farmers transformed their existing, deep-rooted connections into post-disaster assistance. This, in turn, generated the idea of the therapeutic community, helping community members cope in the aftermath. This research indicated the need to further examine how older adults in disaster settings can be viewed as assets with community knowledge and skills as opposed to solely as a vulnerable population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".