“If Somebody Needed Help, I Went Over”: Social Capital and Therapeutic Communities of Older Adult Farmers in British Columbia Floods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 it