Response concerning: Signild Vallgårda, The Danish trans-fatty acids ban: alliances, mental maps and co-production of policies and research
Bibliographic record
Abstract
In this paper, Signild Vallgårda (SV) investigates why a ban against the use of industrially produced trans fatty acids in foods was introduced in Denmark as the first country in the world. SV correctly states that our part of, and activity in that process, represent a combination of scientific work and ‘policymaking’. We, however object to some of the main conclusions given in the title of the paper and spelled out in the following sentence from the abstract: ‘Danish researchers interpreted the research in a way to suit their “mental map” and to support their initially set goal to reduce industrially produced trans fats’; and further in the last sentence in the paper, ‘the evidence of the harmfulness of trans fats was interpreted strongly, ruminant trans fats were ignored and research results were sometimes misread’.<br/><br/>We find that SV omits some crucial facts that undermine some of the main conclusions in her paper. We also find that several statements unrightfully question our scientific credibility and honesty.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.033 | 0.034 |
| Insufficient payload (model declined to judge) | 0.027 | 0.014 |
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 source (direct Gemma or distilled Codex), 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".