MétaCan
Menu
Retour à la cohorte
Enregistrement W1739241353 · doi:10.18438/b8hc7v

The Academic Reward System is the Primary Influence Toward Faculty Non-Participation in Institutional Repositories

2007· article· en· W1739241353 sur OpenAlexvenueno aff
Kurt Blythe

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2007
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueScientific Computing and Data Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDSPACEContext (archaeology)Library sciencePeriod (music)Scholarly communicationSocial scienceSociologyWorld Wide WebPolitical scienceComputer scienceGeographyArtPublishingArchaeology

Résumé

récupéré en direct d'OpenAlex

Objective – To better understand the lack of faculty participation in Cornell University’s DSpace institutional repository (IR), and to learn if this lack of participation is peculiar to Cornell or reflective of a larger trend in faculty non-participation in IRs. 
 
 Design – Comparative analysis and interviews. 
 
 Setting – Cornell University’s DSpace IR and sciences, social sciences, and humanities faculties; and DSpace installations at 7 other universities.
 
 Subjects – The DSpace IR at Cornell University and at 7 other locations. Eleven sciences, social sciences, and humanities faculty members at Cornell University. 
 
 Methods – The authors analyzed data over a fifteen-month period from Cornell’s DSpace IR to determine the total deposits, the types of objects deposited, the communities and collections that received deposits, the frequency of deposits, the IP addresses which made deposits, and how often objects in the IR were viewed. These data were compared to equivalent data taken from seven other IRs on all aspects except deposits from IP addresses and how often objects were viewed. Finally, 11 Cornell faculty members from various departments in the sciences, social sciences, and humanities were interviewed over a two-month period to provide context to the comparative analysis.
 
 Main results – At the time of the study, the IR at Cornell was organized into 193 communities of collections. These collections numbered 196, with 139 of them holding a combined total of 2646 objects: The other 57 collections were empty. While the IR as a whole showed steady growth, 77% of Cornell’s collections reflected a plateau growth pattern of primarily “one-time deposits,” approximately 18% exhibited a stair-step growth pattern of “periodic batch additions of material,” approximately 3% showed steady growth, and 1.4% were “uncatagorizable.” Five-hundred nineteen unique IP addresses made deposits to Cornell’s IR over the course of the fifteen-month study, but 50% of these deposited only one object, and only 32 IP addresses deposited 10 or more objects. 
 
 Of the other IRs studied, the lowest number of communities is zero and the highest is 390, the number of collections ranged from 10 to 282, and the number of objects ranged from 500 to 32,676. In most statistical categories, Cornell fell in the midrange. The two repositories with the fewest communities and collections – zero communities and 18 collections in one instance, and 6 and 10 in the other – are the only two with no empty collections. The repository with the most communities and collections also had the most empty collections (58%). The repository with the most objects was the one with zero communities and only 18 collections; and the repository with the fewest objects was the one with only 6 communities and 10 collections. The third largest IR, with 3111 objects, had far and away the highest rate of steady growth (16.7%); while the IR with the most objects had the highest rate of stair-step growth (56.3%), and was the only IR to have a higher percentage of growth in any category other than plateau. 
 
 Interviews with faculty indicated that they do not make deposits to IRs for a number of reasons. Faculty considered their primary audience to be their peers, so access to their scholarship was largely considered a “non-issue” as it was adequately provided through personal Web pages, subject repositories, or journal literature. Likewise, long-term preservation was not an overarching area of concern. The chief factors for not using an IR, however, all revolved around restrictions brought on by the academic reward system. Questions of copyright and whether depositing objects qualifies as publishing, thereby hindering efforts to publish in journals, were paramount, as were fears that depositing scholarship alongside less rigorous works in a catch-all IR would diminish the work and the reputation of the scholar by association. Hesitancy to make work available before it had been certified and peer-reviewed was also a foremost concern. 
 
 Conclusion – Although objects in Cornell’s DSpace are accessed both locally for items that are tied into the curriculum, and outside of the university for items that are of national (and international) interest, the repository was not supported well by the faculty. The majority of the collections defined in Cornell’s IR were under populated, and what growth was evident arose primarily from deposits made by non-faculty. The reasons for this were manifold, but centered primarily on the established culture of the academic reward system, which encourages publishing in recognized journals and does little to foster thoughts for long-term preservation or dissemination outside of a given scholar’s peer group. These issues were evident in faculty concerns that depositing materials in an IR might prevent later publication in a journal; the idea that depositing scholarship in a non-vetted repository would diminish that work by association with less scholarly materials; the feeling in some fields that it would be irresponsible to provide access to any unfinished, non-vetted work; the thought that IRs are not sufficient to the task of certifying scholarship; and the concern that deposit in an IR might lead to plagiarism or the loss of initiative on unpublished ideas.

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)0,014
score de la tête « metaresearch » (Gemma)0,012
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Communication savante
Catégories consensuellesCommunication savante
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,546
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0140,012
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0020,120
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
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 Opus0,068
Tête enseignante GPT0,377
Écart entre enseignants0,309 · 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'étudeSans objet
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2007
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueEvidence Based Library and Information PracticeMême sujetScientific Computing and Data ManagementTravaux en français237 207