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Response concerning: Signild Vallgårda, The Danish trans-fatty acids ban: alliances, mental maps and co-production of policies and research

2018· article· en· W2782759144 on OpenAlexaff
Steen Stender, Jørn Dyerberg, Arne Astrup

Bibliographic record

VenueEvidence & Policy · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Law Studies
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsDanishProduction (economics)BusinessPolitical scienceEconomicsPhilosophyMicroeconomics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.171
GPT teacher head0.456
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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