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Record W2096776134 · doi:10.1162/1526380054794943

Cancer and Global Environmental Politics: Proposing a New Research Agenda

2005· article· en· W2096776134 on OpenAlex
Peter Dauvergne

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

VenueGlobal Environmental Politics · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Conflict Studies
Canadian institutionsSocial Sciences and Humanities Research Council
Fundersnot available
KeywordsPoliticsWorryPolitical scienceGlobal politicsGlobal healthConsumption (sociology)International relationsCancerEnvironmental politicsEconomic growthPolitical economyDevelopment economicsSocial scienceSociologyEconomicsHealth careMedicineLaw

Abstract

fetched live from OpenAlex

More than six million people die of cancer every year. Over the next two decades, the World Health Organization predicts global cancer rates will rise to 10 million deaths annually. What is the impact of the global political and economic processes of environmental change on cancer rates? Why, given the strong intuitive reasons to worry about the carcinogenic effects of global environmental change, is there so little research on this topic? What is the political role of science, corporations, nongovernmental organizations and international institutions on cancer research and cancer rates? What is the impact of global patterns of trade, financing, production and consumption on research and rates? This article charts the current social science literature on cancer and global environmental change with the hope of encouraging scholars of global environmental politics to pursue a new research agenda around questions like these.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.108
GPT teacher head0.472
Teacher spread0.365 · 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