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Record W4414612874 · doi:10.1111/1745-5871.70036

PFAS ubiquity as corporate accomplishment: Whiteness in early Teflon advertisements

2025· article· en· W4414612874 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

VenueGeographical Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsSGS (Canada)
Fundersnot available
KeywordsCognitive reframingConstruct (python library)State (computer science)Work (physics)Chemical warfareConsumer Culture

Abstract

fetched live from OpenAlex

Abstract In recent years, per‐ and polyfluoroalkyl substances (PFAS) contamination has attracted significant media attention. However, little is known about the efforts of chemical corporations to produce consumer markets for PFAS in the Global North. In this article, we reframe PFAS contamination by shifting from characterising PFAS as “emerging contaminants” owing to a prior state of public ignorance, to understanding ubiquitous PFAS exposure as an indicator of environmental violence under colonial racial capitalism. We examine how chemical manufacturers constructed U.S. consumer markets for PFAS‐containing products in the aftermath of World War II. To better understand contemporary PFAS contamination, we turn to the initial military applications of PFAS in the Manhattan Project and examine subsequent corporate efforts to construct civilian markets for synthetic nonstick products in the mid‐twentieth century. Using archival data from advertising campaigns for nonstick cookware, we analyse the roles of white, heterosexual, feminine imagery in early market development. We argue that imagery of white women facilitated the initial normalisation and expansion of domestic chemical markets in the post‐war period. We elevate the work of corporate actors to construct, maintain, and expand markets for PFAS, arguing that these organisations—and the systems that permit their behaviour—are worthy of further study.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.136
GPT teacher head0.454
Teacher spread0.318 · 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