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Record W2009987649 · doi:10.1177/0306312709345359

Ghosts in the Machine

2009· article· en· W2009987649 on OpenAlex
Sergio Sismondo

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

VenueSocial Studies of Science · 2009
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsGovernment of Canada
Fundersnot available
KeywordsEpistemologySociologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Leemon McHenry (2009) raises a set of issues about the normative stances I take in my recent paper on publication planning in the pharmaceutical industry (Sismondo, 2009). In objecting to my stances, McHenry also sug gests that the problems faced in medical research show the constructivist tradition in Science and Technology Studies (STS) to be crucially flawed. His position on my normative stances is an intuitively attractive one, but I think that it misses important features of clinical research and publication, and so misses opportunities. First, though, while it might merit more dis cussion, let me set aside his position on constructivism. McHenry's quick argument against constructivism is that it cannot allow one to distinguish between 'genuine and sham' science, or between ordinary choice-laden science and misconduct. However, we can easily make a concrete version of these distinctions by relying on community norms, standards, or ideals: in general, behavior that constitutes scientific misconduct fails to live up to scientific norms. We can even go further, and argue that some community norms, standards, or ideals don't live up to others, or don't live up to extra-scientific ideals. In so doing, constructivists can critically engage with academic medicine if they choose to. I therefore applaud the work of people such as McHenry and his col league Jon Jureidini, and the many other vigilant critics of industry-sponsored trials (for a few citations, see McHenry's [2009] comment). I happily join them when the opportunity arises. The problem is not that criticism of the flaws of individual trials or publications is too bold a move, but that restrict ing criticism to flawed trials and publications is too cautious. The thorough ghost management of the pharmaceutical literature suggests that we should want to go much further. If I did not make that clear enough in my paper, I thank McHenry for pushing me to amplify the point. McHenry (p. 000) says, 'If the results of industry-sponsored clinical tri als were reported honestly, then aside from the question of deception and plagiarism, ghostwriting would not present a serious concern for advancing knowledge.' I take issue with that assumption.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
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 head0.670
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