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Record W2106525269 · doi:10.1177/0306312708101047

Ghosts in the Machine

2009· article· en· W2106525269 on OpenAlexaff
Sergio Sismondo

Bibliographic record

VenueSocial Studies of Science · 2009
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsQueen's University
Fundersnot available
KeywordsEpistemologySociologyComputer sciencePsychologyPhilosophy

Abstract

fetched live from OpenAlex

Publication of pharmaceutical company-sponsored research in medical journals, and its presentation at conferences and meetings, is mostly governed by 'publication plans' that extract the maximum amount of scientific and commercial value out of data and analyses through carefully constructed and placed papers. Clinical research is typically performed by contract research organizations, analyzed by company statisticians, written up by independent medical writers, approved and edited by academic researchers who then serve as authors, and the whole process organized and shepherded through to journal publication by publication planners. This paper reports on a conference of an international association of publication planners. It describes and analyzes their work in an ecological framework that relates it to marketing departments of pharmaceutical companies, medical journals and publishers, academic authors, and potential audiences. The medical research described here forms a new kind of corporate science, designed to look like traditional academic work, but performed largely to market products.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaScience and technology studies
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptInsufficient payload (model declined to judge)
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
models splitAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0060.020
Scholarly communication0.0120.026
Open science0.0020.008
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0320.008

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 head0.670
GPT teacher head0.660
Teacher spread0.010 · 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

Labeled directly by 2 models reading the full record.

Science and technology studiesInsufficient payload (model declined to judge)

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Not applicable
Domainnot available
GenreEmpirical · Other

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

Citations298
Published2009
Admission routes1
Has abstractyes

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