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Enregistrement W2418064873

Collaborative research and the scholarship of engagement: challenges for academic researchers

2015· dissertation· en· W2418064873 sur OpenAlexaboutno aff
Rose Marie Tapp-Neville

Notice bibliographique

RevueMemorial University Research Repository (Memorial University) · 2015
Typedissertation
Langueen
DomaineSocial Sciences
ThématiqueService-Learning and Community Engagement
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésScholarshipEngaged scholarshipGeneral partnershipCLARITYAllianceCommunity engagementPublic relationsQualitative researchPopulationUnit (ring theory)Value (mathematics)SociologyPedagogyPsychologyPolitical scienceMedical educationSocial scienceMedicineMathematics education
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The purpose of this qualitative, interpretive study was to explore the challenges associated with collaborative research and the scholarship of engagement particularly for academic researchers, to determine the value placed on collaborative research by both academics and community partners, and to investigate how community-university partnerships can be sustained. Academic researchers and community partners from a Community University Research Alliance (CURA) project in a Faculty of Education at a Canadian university, a CURA fellow graduate student, a representative from a knowledge mobilization unit at a university, and a Social Sciences and Humanities Research Council (SSHRC) official were included in the study population. Sixteen interviews in total were conducted and analyzed.
\nThe findings of this study suggest that collaborative research is challenging work. Administrative, relationship-related, cultural, and ethical challenges were highlighted. Administratively, it can be very difficult to manage a partnership with multiple projects, and its players having varying levels of understanding of collaborative research. One of the greatest administrative challenges is dealing with the changeover of players, and engaging participants who come to the project later. Clarity of expectations can be challenging since even when one attempts to develop protocols, it can be difficult to predict all issues that may arise. This study demonstrates that academics and community partners do not have a good understanding of each other’s cultural realities which can be the source of frustration when individuals do not understand why the other partner is behaving in a certain manner. Dealing with findings that may not be favourable to the community partner creates ethical challenges.
\nThis study demonstrates that the value of collaborative research depends on the perspective of the participant. Some academic researchers and community partners welcome the opportunity to work together in the co-creation of knowledge since they recognize that a more enriched product can be the end result. Other university researchers, holding steadfast to more traditional research, sometimes only engage in collaborative work to gain access to funding, and very quickly resort to more traditional methodologies. For some community partners, the research has little value to guide practice.
\nAmong factors highlighted for contributing to the potential success of collaborative partnerships, the level of participant buy-in is noted as having a definite effect. Minimizing the number of partnerships and allowing more than five years may be needed to grow sustainable partnerships. Looking for the “right fit” between partners where interests align could help. Knowledge mobilization units could be beneficial to help connect partners. The creation of memorandums of understanding, advisory committees, and a project manager position are highly recommended. Fostering strong leadership, incorporating succession planning, and the need for ongoing dialogue to help engage participants and create ownership are important. Time release supports for both academics and community partners, and university support through promotion and tenure practices that reward collaborative research involvement can help sustain community-university partnerships.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,043
score de la tête « metaresearch » (Gemma)0,006
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Études des sciences et des technologies, Intégrité de la recherche
Catégories consensuellesÉtudes des sciences et des technologies
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,616
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0430,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,003
Études des sciences et des technologies0,0100,004
Communication savante0,0000,001
Science ouverte0,0040,001
Intégrité de la recherche0,0010,006
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,226
Tête enseignante GPT0,417
Écart entre enseignants0,191 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeQualitatif
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2015
Routes d'admission1
Résumé présentoui

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