Why place matters: A rurally-orientated analysis of COVID-19’s differential impacts
Bibliographic record
Abstract
This paper considers the implications of COVID-19 during the early stages – or ‘first wave’ – of the 2020 pandemic in relation to the enduring urban/rural dichotomy within high-income economies. Drawing on popular media/news stories and political discourse that emerged during this time, we examine how dominant constructions of dichotomised places (urban/rural) have been transformed in ways that highlight how rural places are positioned in contestations over resources and control of spaces. This examination is contextualised within an understanding of the enduring healthcare maldistribution between urban and rural places in geographically large and sparsely populated high-income countries, which renders many rural locales decidedly vulnerable when it comes to the testing/diagnosis, treatment and management of COVID-19. We argue that scholars engaged in place-sensitive research have a critical role to play in working with and empowering rural communities to increase broader public and political understanding of precisely why place matters during public health crises.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".