Notice bibliographique
Résumé
Abstract Over the past few decades, scientific researchers have come under increasing pressure to commercialise their findings. This pressure and an increase in academic–industry connections have raised a number of concerns, including a potential loss of funding for basic science, the increased likelihood of researchers and universities finding themselves in (real or perceived) conflicts of interest and a potential loss of public support for research. In the human genetic research context, additional concerns have been raised including the legality of gene patents and their effect on innovation, the potentially premature marketing of genetic technologies and the readiness of health‐care systems, physicians and society for the increasing number and range of genetic testing options. While some of these concerns have proven less worrisome than others, the full extent of the impact of commercialisation of human genetic research is not yet known and there is much room for further research in this area. Key Concepts Commercialisation of scientific research can essentially be understood as the conversion of research findings into a commercial product or service (Downie and Herder, 2007) and can involve industry–university partnerships, patenting of research findings or spin‐off companies created as a result of research. Commercialisation of scientific research has grown significantly in recent years and is increasingly being prioritised by public funding bodies. As a result, the scientific community is under pressure to demonstrate the commercial value of their work. This is often referred to as ‘commercialisation pressure’. In the genetic research context, gene patenting has raised a lot of controversy in terms of its moral, ethical and legal validity. The legality of these patents has been debated around the world, and different jurisdictions appear to be coming to different conclusions on this issue. One concern that is frequently raised regarding gene patenting is its potential to negatively impact innovation by creating an ‘anticommons’ (Heller and Eisenberg, 1998). The ‘anticommons’ concern is essentially the idea that the growth of intellectual property protection will hinder researchers from accessing necessary research inputs, thereby slowing scientific progress and innovation. This concern has received a great deal of attention; however, recent research raises questions about the extent to which this concern has actually manifested. There has also been a lot of ‘hype’ surrounding genetic research, which has frequently been portrayed to the public in an overly optimistic manner in terms of its potential benefits and timelines in which these benefits are likely to materialise. This phenomenon is not necessarily the result of any intention to mislead the public but rather the product of many different pressures and incentive structures that scientists, research institutions and the media are operating under. Direct‐to‐consumer genetic testing has also raised concerns in terms of the marketing strategies employed by companies offering these tests and their ability to actually deliver useful health information to consumers. As a result, some regulatory bodies are taking a firm stand against companies marketing these tests, while others appear to be taking a more permissive stance.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,051 | 0,139 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,012 |
| Communication savante | 0,017 | 0,011 |
| Science ouverte | 0,003 | 0,010 |
| Intégrité de la recherche | 0,008 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,036 | 0,008 |
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 source (Gemma direct ou Codex distillé), 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 ».