Are we ready to be wrong? Extended peer community for quality science-advice in uncertainty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper delves into the challenges of achieving inclusion within science-advice institutions, particularly focusing on the International Council for the Exploration of the Sea (ICES). It explores the normative and practical implications of broadening the epistemic space to incorporate diverse ways of knowing in uncertain contexts. Traditional science-advice often relies on strict quantification and institutionalized expertise, limiting the recognition of alternative perspectives. The study proposes an alternative view rooted in post-normal science, advocating for the adoption of an extended peer community model. Despite ICES's efforts to enhance stakeholder engagement through its Stakeholder Engagement Strategy, gaps remain in effectively valuing epistemic diversity. By analyzing a historical case involving the revision of fishing quotas for Northeast Atlantic mackerel, the paper illustrates the limitations of strict quantification in addressing complex and uncertain problems. It recommends a participatory approach informed by post-normal science principles and incorporates the concept of “epistemic injustice” in Miranda Fricker’s work (Fricker, 2003, 2007) to the discussion to underscore the ethical imperative of inclusive decision-making. Ultimately, the paper advocates for post-normal science approaches to better address contemporary challenges in science-advice institutions when the problem is deeply uncertain and complex. • Post-normal science approach advocated for inclusive decision-making in science-advice institutions. • Extended peer community model proposed to incorporate diverse ways of knowing in uncertain contexts. • ICES's efforts to enhance stakeholder engagement highlighted, but gaps in valuing epistemic diversity remain. • Introduction of Fricker’s concept “epistemic injustice” to frame the ethical imperative of inclusive decision-making. • Case study illustrates limitations of strict quantification in addressing complex, uncertain problems.
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.
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 | 0.019 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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