Trust, Transparency and Transnational Lessons from COVID-19
Bibliographic record
Abstract
The article engages in an exercise in reflexivity around trust and the COVID-19 pandemic. Common understandings of trust are mapped out across disciplinary boundaries and discussed in the cognitive fields in the medical and social sciences. While contexts matter in terms of the understandings and uses made of concepts such as trust and transparency, comparison across academic disciplines and experiences drawn from country experiences allows general propositions to be formulated for further exploration. International health crises require efforts to rebuild trust, understood in a multidisciplinary sense as a relationship based on trusteeship, in the sense of mutual obligations in a global commons, where trust is a key public good. The most effective responses in a pandemic are joined up ones, where individuals (responsible for following guidelines) trust intermediaries (health professionals) and are receptive to messages (nudges) from the relevant governmental authorities. Hence, the distinction between hard medical and soft social science blurs when patients and citizens are required to be active participants in combatting the virus. Building on the diagnosis of a crisis of trust (in the field of health security and across multiple layers of governance), the article renews with calls to restore trust by enhancing transparency.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".