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Manufacturers' response to criticism

2004· review· en· W2018939834 on OpenAlexaff
Iain Moppett, Jennie Spendlove

Bibliographic record

VenueAnaesthesia · 2004
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsQueen's University
Fundersnot available
KeywordsCriticismRebuttalMedicineConstructive criticismConstructiveTask (project management)LawManagementComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Following the recent publication of a pair of letters (Knaggs & Bennett, Anaesthesia 2004; 59: 305; Solomans, Anaesthesia 2004; 59: 305) that contained a criticism of a manufacturer and a rebuttal, we were intrigued to see how often manufacturers are prepared to accept criticism in published correspondence. A brief survey of correspondence published in Anaesthesia over the last 4 years has found the following results: of 52 letters commenting on or criticising equipment or drugs, with accompanying manufacturers' replies, half were dismissed by the manufacturer; in 12 the criticisms were accepted as fair; in the remaining 14 responsibility was deemed shared. In several of the rebuttals, the manufacturers completely ignored the criticism, and provided a ‘politician’s' response by answering a different question. Some of this would appear to be a reluctance to admit to anything which might prove legally damaging. Clearly, manufacturers are not at fault every time a piece of equipment or a drug is criticised, but the proportion and manner of such rebuttals seems inappropriate. All original letters for publication undergo some element of peer review prior to publication. We feel that it is time for the Editor-in-Chief to take the manufacturers to task before publication, where replies are clearly unsatisfactory. We thank Dr Moppett and Ms Spendlove for their comments. Manufacturers are always given the chance to respond to criticism of their products, and the vast majority do so in a timely and constructive fashion. Replies are edited for style and format. However, we are also motivated by the need for problems with equipment to be aired within a reasonable time of their being reported, and the delays imposed by waiting for the occasional tardy response mean that we do not always have time to enter into a lengthy debate about whether the manufacturer has fully addressed the point at issue. In practice, of course, the manufacturer's response often speaks for itself, and readers are at liberty to draw the same conclusions as Dr Moppett and Ms Spendlove. M. H. Nathanson Editor and D. Bogod Editor-in-ChiefAnaesthesia AAGBI London, UK

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

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)0.046
metaresearch head score (Gemma)0.279
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.242

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.279
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0040.004
Science and technology studies0.0050.006
Scholarly communication0.0130.006
Open science0.0070.007
Research integrity0.0600.039
Insufficient payload (model declined to judge)0.0510.054

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 head0.521
GPT teacher head0.608
Teacher spread0.087 · 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

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2004
Admission routes1
Has abstractyes

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