Fear-Responses to Bat-Originating Coronavirus Pandemics with Respect to Quarantines Gauged in Relation to Postmodern Thought—Implications and Recommendations
Bibliographic record
Abstract
Fear-responses to bat-originating coronavirus pandemics with respect to quarantine imposition are gathered and interpreted from large datasets, identified and disseminated by media. Responses are effectively gauged using postmodern thought with a continuum ranging from people’s resilience to define their own perspectives to public views being socially conditioned from media persistence in maintaining fear. Public responses to the 2003 SARS pandemic generally presumed and supported resilience of citizens’ perspectives. In contrast, from late 2019 to mid-2022, public responses to the COVID-19 pandemic were media-determined, promoting fear. In this regard, reactions to the COVID-19 quarantines are contrasted to the hospital isolations of SARS. The primary source of the difference was the major polarizing influence by social media of the WHO policy makers’ pronouncements and of healthcare providers’ statements directing media spotlight in their guidance of public response to COVID-19 throughout the pandemic, unlike during SARS. An investigation of cognitive bias regarding the psychological and societal implications related to this migration from resilience to fear regarding public responses to novel bat-originating coronavirus pandemics elicits recommendations concerning future quarantine dictates. These recommendations are dependent on appropriate encouragement of hopeful resilience through evidence based practice with respect to one extreme of the postmodern thought continuum.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".