Investigating the Experiences of Ontario's Rural Residents during the COVID-19 Pandemic
Bibliographic record
Abstract
Rural residents are often more disadvantaged in responding to challenges compared to urban dwellers. Using a case study, our study aims to enhance the understanding of the COVID-19 pandemic’s effects on rural residents. The objectives of our study are to 1) explore rural residents' experiences as it relates to communication, access to government services, food security, and transportation; 2) examine the economic effects on rural populations on their income and employment. An online survey was completed anonymously through a google forms link by Middlesex County residents sample size N= (436). The survey questionnaire contained socio-demographics-related questions and closed-ended and open-ended questions. The quantitative data were analyzed using SPSS, while qualitative data were analyzed using thematic analysis. The pandemic has affected participants’ economic and social lives in significant ways. The primary reported issues were physical and mental health, employment and less income, transportation/travel inconvenience, access to food and essential needs, and social isolation.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".