Living in the shadow of rural digital vulnerability: Navigating technology needs and resources
Bibliographic record
Abstract
As internet access becomes increasingly required for full societal participation, the risks of digital exclusion are accentuated for some populations, such as rural citizens. The objective of this qualitative descriptive study was to explore the digital experiences of rural residents in a Western Canadian province with differing broadband speeds. Participants were recruited in follow-up to an online survey which asked for interest in participation in focus groups to further discuss experiences with digital technologies. Rural adults (n = 32) with connectivity speeds both above and below the Canadian definition of high-speed participated in one of six focus groups. Transcripts from the recorded focus groups were thematically analyzed. The overarching theme that described participants' digital experiences was living in the shadow of rural digital vulnerability, or the interaction between their needs and available resources, with three sub-themes further detailing their experiences. Rural conditions threatened digital vulnerability, and produced harm when there was mis-alignment between participants’ needs and available resources. Compounding their susceptibility to vulnerability, were pressures to engage digitally, which participants described coming from services, work, and family and friends, and tech companies and emerging technology. Participants navigated threatened vulnerability by accommodating the technology to fit their lives and by adapting their lives to fit the technology within their infrastructure limitations . Overall, the digital experiences of rural residents highlight the role of context and individual agency in predisposition to risk, advancing a nuanced understanding of vulnerability.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".