Ethics in Forced Migration Research: Taking Stock and Potential Ways Forward
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Notice bibliographique
Résumé
Migration research poses particular ethical challenges because of legal precarity, the criminalization and politicization of migration, and power asymmetries. This paper analyzes these challenges in relation to the ethical principles of voluntary, informed consent; protection of personal information; and minimizing harm. It shows how migration researchers - including those outside of academia - have attempted to address these ethical issues in their work, including through the recent adoption of a Code of Ethics by the International Association for the Study of Forced Migration (IASFM). However, gaps remain, particularly in relation to the intersection of procedural and relational ethics; specific ethical considerations of big data and macrocomparative analyses; localized meanings of ethics; and oversight of researchers collecting information outside of institutional ethics boards. The paper concludes with the following recommendations: Institutional Research Ethics Boards should familiarize themselves with the particular ethical challenges in migration research, as well as available resources, such as the IASFM Code of Ethics. Ethics boards should include researchers and community representatives who are familiar with migration in reviews of related projects.Academic and training programs in migration studies should include sessions and resources on migration-specific research ethics.Nonacademic organizations, including migrant-led organizations, should provide information resources and training to their staff and clients to ensure that they understand procedural ethics requirements, relational ethical principles, as well as the rights of those asked to participate in research. Organizations conducting their own research should establish ethics review processes and relational ethics norms.A leading migration studies center or institution should map existing ethical guidelines and processes in different countries and contexts to be better aware of overlap and gaps. This mapping should take the form of an open access, interactive database, so that information can be accessible and updated in real time.Researchers should engage in more dissemination of lessons learned on ethics in migration. While there is some emerging consensus on key ethical principles for migration research, it is in their application that researchers face dilemmas. Honest reflection and sharing of these experiences will help researchers to anticipate and manage similar dilemmas they encounter while undertaking research.Researchers at all stages of their careers should not undertake migration research without having first reviewed some of the literature on ethics and migration, which is partially cited in this paper.Research centers should facilitate dialogue on ethical issues in languages other than English, particularly languages most spoken by people in migration, and by people who are underrepresented in formal ethics processes and debates, especially those with direct experience of migration.
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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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 découle