“No Entry into New South Wales”: COVID-19 and the Historic and Contemporary Trajectories of the Effects of Border Closures on an Australian Cross-Border Community
Bibliographic record
Abstract
Given its intensity, rapid spread, geographic reach and multiple waves of infections, the COVID-19 pandemic of 2020/21 became a major global disruptor with a truly cross-sectoral impact, surpassing even the 1918/19 influenza epidemic. Public health measures designed to contain the spread of the disease saw the cessation of international travel as well as the establishment of border closures between and within countries. The social and economic impact was considerable. This paper examines the effects of the public health measures of “ring-fencing” and of prolonged closures of the state border between New South Wales and Victoria (Australia), placing the events of 2020/21 into the context of the historic and contemporary trajectories of the border between the two states. It shows that while border closures as public-health measures had occurred in the past, their social and economic impact had been comparatively negligible due to low cross-border community integration. Concerted efforts since the mid-1970s have led to effective and close integration of employment and services, with over a quarter of the resident population of the two border towns commuting daily across the state lines. As a result, border closures and state-based lockdown directives caused significant social disruption and considerable economic cost to families and the community as a whole. One of the lessons of the 2020/21 pandemic will be to either re-evaluate the wisdom of a close social and economic integration of border communities, which would be a backwards step, or to future-proof these communities by developing strategies, effectively public health management plans, to avoid a repeat when the next pandemic strikes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".