Misleiding herbekeken: een dialoog tussen onderzoeks-ethische ondersteuning en praktijk
Notice bibliographique
Résumé
The researcher that will be hired will lead research activities in the domain of research ethics in two different projects. The main focus will be on a project funded by the CELSA Alliance (KU Leuven - Jagiellonian University Medical College) that will focus on the ethical aspects related to research strategies that purposefully mislead research participants. Although methodologies that use deception in their design could potentially increase relevant scientific knowledge in a huge number of areas, there is a lack of understanding about the conditions under which such a methodology is justified and a lack of clarity about what constitutes an appropriate context in which research participants can be deceived. Therefore, the use of deception in research studies has been heavily criticized because of ethical concerns regarding its use; because of the lack of proper informed consent and the fact of misleading the participant to the real purpose of the study. More recently, the development of the General Data Protection Regulation challenges the use of deception even more. This project will allow (1) to systematically identify research studies that used deception; (2) to investigate the experiences of researchers who have used a methodology in which deception was used; and (3) to systematically map research ethics guidelines and recommendations in order to analyse to what extent and the ways in which recommendations deal with the use of deception in research. This project will be jointly supervised with professor Jan Piasecki (Jagiellonian University Medical College) and professor Dieter Baeyens (Faculty of Psychology and Educational Sciences, KU Leuven). Alongside the first project, the researcher will be involved in a bilateral Flanders (Belgium)- Canada project funded through the Research Foundation Flanders on the ethical aspects related to the research use of crowdsourced medical data for biomedical research. Smartphone applications for health are being increasingly used as a platform for collecting and sharing large volumes of crowdsourced personal health data for biomedical research and algorithm training. Consumer genetics products are similarly allowing individuals to have direct access to their own genetic data and to share such data with researchers. Using smartphone and genetic data in these ways presents numerous opportunities to expand biomedical knowledge, though it also raises certain risks. Some of these include risks to personal privacy and risks associated with unclear ethical and legal obligations on the part of app developers and researchers. The research activities will be done through a multi-disciplinary lens and by studying the ethical and policy concerns both from a theoretical and from an empirical perspective through interviews with experts and stakeholders.
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 | 0,006 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,005 |
| 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 ».