Notice bibliographique
Résumé
The whole aim of practical politics is to keep the populace alarmed (and hence clamorous to be led to safety) by menacing it with an endless series of hobgoblins, most of them imaginary. - H. L. Mencken[dagger] CONTEXT It is a common ritual among today's academics to submit research proposals to a group of colleagues, the Institutional Review Board (IRB; REB in Canada). When IRBs were first created in 1974,1 they were directed to assess whether a researcher's proposed project would expose the public to greater than everyday Over the last thirty years, IRBs have evolved to review research proposals against criteria well beyond the scope of their original mandate or their ostensible purpose.2 For example, instead of assessing whether proposed research would expose the public to greater than everyday IRBs now ask whether proposed research would expose members of the public to even risk. In practice minimal risk is a euphemism for zero risk, which is an impossible objective to achieve.3 Likewise, IRBs have expanded the review process beyond the issue of publie safety to pursue more nebulous agendas, including whether the proposed research is worthwhile. They now weigh expected social benefits, legal liability, and similar issues, presuming to judge at the outset that which can only be determined by examining the results. The broadening scope of IRB inquiry can charitably be described as creep,4 and because this expansion has happened in small steps over thirty years, the successive impositions were seldom challenged. However, the cumulative effect is striking,5 and there is no sign this mission creep has been stalled. Such subterfuge is typical of the way the research ethics enterprise has expanded over the years, always with the result that control of inquiry is increased with no documented evidence of enhanced subject safety. Today, particularly in the field of non-medical research, the institutional review process is more accurately described as censorship than safety screening.6 My intent here is to (1) describe how various distortions are used to defend and justify the ethics reviews, and (2) highlight some costs of the ethics enterprise that are routinely ignored. I will focus on social science and humanities research, in part because of my interests, but also because these disciplines seem most vulnerable to unwarranted censorship. When all of the results, intended and otherwise, are considered, it is clear that the constraints imposed on academic inquiry have not been accompanied by an increase in public benefits. I. BENEFITS The benefits of IRBs can be divided into two sets. The first set includes benefits IRB supporters claim accrue to the public despite the lack of reliable evidence that such benefits have materialized. My attention to these will be mainly to critique the shortcomings of the claim that procedure X improves public safety. The second set will concern benefits that accrue exclusively to regulators. These benefits are far more obvious, though they remain unacknowledged by IRB supporters. A. What is the Evidence, and How Do We Evaluate It Before I analyze the claimed benefits and the actual benefits to regulators, it is important to establish a clear understanding of what constitutes reliable evidence that can support a claim that IREs produce certain benefits. By definition, identifying something as a requires some variation of a pre-post assessment. That is, one needs the identification of a null or undesirable state to begin with, a manipulation, and then a secondary assessment that documents improvement. The former shows evidence of a need, and the latter shows evidence of the effectiveness of the manipulation, in this case the ethics review. The general claimed benefit is improved public safety, and I think the burden of proof for that is on the claimant. What is the evidence and what is its validity? …
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».