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Record W2118482318 · doi:10.1016/j.yrtph.2015.07.026

Manufacturing doubt about endocrine disrupter science – A rebuttal of industry-sponsored critical comments on the UNEP/WHO report “State of the Science of Endocrine Disrupting Chemicals 2012”

2015· letter· en· W2118482318 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRegulatory Toxicology and Pharmacology · 2015
Typeletter
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsEnvironment and Climate Change CanadaUniversity of New BrunswickVancouver Aquarium
Fundersnot available
KeywordsRebuttalCausality (physics)Perspective (graphical)State (computer science)EpistemologyPositive economicsSociologyEnvironmental ethicsPolitical scienceLawEconomicsPhilosophyComputer science

Abstract

fetched live from OpenAlex

We present a detailed response to the critique of "State of the Science of Endocrine Disrupting Chemicals 2012" (UNEP/WHO, 2013) by financial stakeholders, authored by Lamb et al. (2014). Lamb et al.'s claim that UNEP/WHO (2013) does not provide a balanced perspective on endocrine disruption is based on incomplete and misleading quoting of the report through omission of qualifying statements and inaccurate description of study objectives, results and conclusions. Lamb et al. define extremely narrow standards for synthesizing evidence which are then used to dismiss the UNEP/WHO 2013 report as flawed. We show that Lamb et al. misuse conceptual frameworks for assessing causality, especially the Bradford-Hill criteria, by ignoring the fundamental problems that exist with inferring causality from empirical observations. We conclude that Lamb et al.'s attempt of deconstructing the UNEP/WHO (2013) report is not particularly erudite and that their critique is not intended to be convincing to the scientific community, but to confuse the scientific data. Consequently, it promotes misinterpretation of the UNEP/WHO (2013) report by non-specialists, bureaucrats, politicians and other decision makers not intimately familiar with the topic of endocrine disruption and therefore susceptible to false generalizations of bias and subjectivity.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.019
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.361
Teacher spread0.341 · 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