"No Silver Bullet Solution": Cruel Optimism and Canada’s COVID-19 Public Health Messages
Bibliographic record
Abstract
Science twines through many of the discussions related to hope for a return to normalcy within public discussions of COVID‑19. The framings of techno-scientific solutions for COVID‑19 are similar to those that are presented to address many societal problems. The messy scientific and regulatory underpinnings of this desired silver bullet rarely make it fully into view. Technoscientific-related hope and its associated affects can operate as a kind of “cruel optimism” (Berlant 2010, 2011). It can be an affective response to return to life as “normal” that is psychologically soothing, even as its enactment may replicate destructive social, political, and economic structures. Hope and technoscience thread throughout the interactions between journalists and health officials in the health press briefings in the first wave of the COVID‑19 pandemic. Technoscientific complexity that challenges the desire to return to normal is rarely brought up in Ontario and Nova Scotia public health briefings. But when it is, health officials in this zone of interaction balance explanations of scientific reality and caution, while attempting to not crush hope for a techno-scientifically mediated return to normal. As such, public health discourse obscures or tempers cruel optimism rather than directly confronting it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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".