Scientific Knowledge and Rural Policy: A Long‐distant Relationship
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 This article examines the extent to which social science evidence is considered by community leaders in small towns and rural areas. It uses secondary analysis of 18 transcriptions from interviews in rural regions within two Canadian provinces to examine what types of support (if any) are used by respondents to justify their claims and assess the extent to which they depend on systematically collected and analysed evidence. The results indicate that the respondents seldom provided justification for their claims and when they did, scientific evidence was infrequently used. Instead, the respondents most often used examples from their personal experience or public meetings as support. Comparative analysis of the two rural region showed that the pattern of support was different in each – with respondents from B ritish C olumbia ( BC ) relying more on personal examples and those from N ewfoundland and L abrador ( NL ) relying more on public presentations or the internet. The results suggest that much work needs to be done to make social science evidence available and useful to those in small towns and rural places. According to those results, the most strategic way to begin is through existing networks, community groups, and local examples.
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 | 0.000 | 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 | 0.001 |
| 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 it