Government Actions and Their Relation to Resilience in Healthcare During the COVID-19 Pandemic in New South Wales, Australia and Ontario, Canada
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Resilience, a system's ability to maintain a desired level of performance when circumstances disturb its functioning, is an increasingly important concept in healthcare. However, empirical investigations of resilience in healthcare (RiH) remain uncommon, particularly those that examine how government actions contribute to the capacity for resilient performance in the healthcare setting. We sought to investigate how governmental actions during the coronavirus disease 2019 (COVID-19) pandemic related to the concept of resilience, how these actions contributed to the potential for resilient performance in healthcare, and what opportunities exist for governments to foster resilience within healthcare systems. METHODS: We conducted case studies of government actions pertaining to the COVID-19 pandemic in New South Wales, Australia and Ontario, Canada. Using media releases issued by each government between December 2019 and August 2020, we performed qualitative content analysis to identify themes relevant to the resilience potentials (anticipate, monitor, respond, learn) and RiH. RESULTS: Direct references to the term 'resilience' appeared in the media releases of both governments. However, these references focused on the reactive aspects of resilience. While actions that constitute the resilience potentials were evident, the media releases also revealed opportunities to enhance learning (eg, a need to capitalize on opportunities for double-loop learning and identify strategies appropriate for complex systems) and anticipating (eg, incorporating the concept of hedging into frameworks of RiH). CONCLUSION: Though fostering RiH through government action remains a challenge, this study suggests opportunities to realize this goal. Articulating a proactive vision of resilience and recognizing the complex nature of current systems could enhance governments' ability to coordinate resilient performance in healthcare. Reflection on how anticipation relates to resilience appears necessary at both the practical and conceptual levels to further develop the capacity for RiH.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| 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