Networks of Neuroscientists: Professional Interactions within an Interdisciplinary Brain Research Institute.
Notice bibliographique
Résumé
Abstract:This paper uses social network analysis to evaluate how the formation of an interdisciplinary brain research institute affected interaction and collaboration among neuroscientists at one Canadian university. The research institute, formed in 2004, has about 100 members representing ten different departments across the university campus. We conducted a whole network survey of the members in 2010, asking them to report on their professional interactions (advice seeking, co-supervising, co-teaching, co-authorship, holding grants, and organizing conferences together) with each of the other members during the five years before and the five years since the foundation of the Institute. Whole network measures examined include density, isolates, average degree and multiplexity. We compared these measures over time. Our findings indicate that professional interactions among the neuroscientists have increased since the founding of the Institute. The main networks of collaborators are now clustered around the three organizational themes of the Institute, which were formalized in 2010. We also examined how individual-level characteristics of the scientists affected professional interaction. We show that departmental co-membership, office co-location and Institute themes are all significant predictors of interaction among neuroscientists at this university since the foundation of the Institute. Social network analysis is a useful tool for evaluating the impact of the establishment of an interdisciplinary institute on scientists relationships.Keywords: interdisciplinary research; social network analysis; collaboration; neuroscienceIntroductionThis project aimed to assess how the formation of the Hotchkiss Brain Institute (HBI; www. ucalgary.ca/hbi) at the University of Calgary (UCalgary) in October 2004 affected professional interactions among neuroscience researchers. Prior to the formation of the HBI, there was no single administrative structure linking neuroscientists who work in different academic departments at UCalgary. Since the formation of the HBI, essentially all neuroscientists working at UCalgary (including new hires) are encouraged to become members of the HBI. Thus, the establishment of the HBI provides a case study through which to examine whether the formation of an explicitly interdisciplinary administrative unit affects professional interactions among scientists at one institution. We conducted a whole network survey of the members of the HBI in November, 2010. We asked all current HBI members (N = 95) to fill out an online survey reporting on their professional interactions with each of the other members since the foundation of the HBI (2005-2010). In addition, for those members who joined the HBI in 2005, we asked about their interactions with other members before the foundation of the Institute. Eighty-one scientists (a response rate of 85%) filled out the survey, indicating their working relationships with other HBI members.We analyzed the data using social network analytic techniques, described below, as well as descriptive statistics. We also examined whether individual-level characteristics of the scientists such as gender, rank, department, office location, research theme, and research pillar affected their relationships with other scientists. Research pillar is a term used in Canada to classify all health researchers into one of four categories - biomedical, clinical, health services or population health (Canadian Institutes of Health Research, 2009). Finally, for each of the professional interaction networks, we examined the positions of those who hold leadership roles in the HBI. We use our results to discuss the effect that the establishment of the HBI has had on professional relationships among neuroscientists at UCalgary. We conclude by reflecting on the usefulness of social network analysis as an evaluation method for interdisciplinary research institutes.BackgroundThe need for collaboration in science is well accepted (Adams, Black, Clemmons, and Stephan, 2005), and many academic fields now encourage interdisciplinary work (Hackett, 2005). …
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 | 0,003 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».