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Enregistrement W2119793079 · doi:10.18438/b8zg7x

Librarian and LIS Faculty Participation in Self-Archiving Practice Needs Improvement

2012· article· en· W2119793079 sur OpenAlexvenueno aff
Annie Hughes

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2012
Typearticle
Langueen
DomaineComputer Science
ThématiqueLibrary Collection Development and Digital Resources
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDirectoryLibrary scienceCitationImpact factorSample (material)Computer scienceWorld Wide WebPolitical science

Résumé

récupéré en direct d'OpenAlex

Objective – To compare librarian and LIS faculty open access (OA) self-archiving behavior. Design – Logistical Regression Analysis. Setting – Twenty top-ranked library and information science journals published in 2006. Subjects – A total of 812 research articles in LIS journals. Methods – For the purpose of data collection, the researchers first compiled a list of library and information science journals utilizing Journal Citation Reports (JCR) from 2006. Twenty journals were selected by considering impact factor and the list compiled was checked against Ulrich’s Periodicals Directory following a similar methodology utilized in a 2007 article by Anita Coleman. The sample included was representative of both library and information science journals, and there were exclusions of 3 types of journals: free online journals where OA participation could not be measured; subscription based journals that do not supply free articles; and annual review journals. Here, OA participation or OA practice is considered to be author self-archiving of articles that are not freely available online. Research articles were included in the sample; however, editorials and book reviews were excluded. The researchers also collected information about the article itself, including the title, name of the journal and name of the author. Only first author’s status as librarian or LIS faculty was considered in data collection. One difficulty in collecting data about the authors was that their professional status was not always clear. The researchers collected information on whether the author’s status was librarian or faculty; when an author’s status was unclear, researchers searched online to determine it. If the author’s status still could not be determined via online searching, the authors chose to exclude those articles. After the articles were collected, Google Scholar was searched in order to determine OA status. The articles that were deemed OA were opened and if the article was downloadable, it was included; otherwise, it was not included. Researchers also avoided linking to articles through their own library portal which would have allowed for access to articles through their own library’s subscription. Other data was collected using Web of Science and included citation information; length of articles; and number of references, authors, and self-citations. Analysis of data was performed utilizing logistic regression. The researchers selected the professional status (librarian or faculty) as the dependent variable, assigning 1 to librarian status and 0 to faculty status. The independent variables included the OA status of an article, citation count, self-citation counts, number of authors, length in pages, and number of references. Researchers also chose to normalize data by adding one citation to every article in the dataset because many did not receive citations. SPSS was utilized as the statistical analysis tool. Main Results – Researchers were able to recognize a divide with regard to where librarians and librarian faculty publish. Librarians tend to avoid journals that focus on information science and publish more in journals related to the practice of librarianship. After performing the logistic regression analysis, researchers also chose to look at the “dichotomous dependent variable” and the “dichotomous predictor variable.” The dependent variable was article availability in OA and the predictor variable is professional status of the author. They ran a 2X2 contingency table and the p-value was below 0.05; therefore, there was a failure to reject the null hypotheses that there is no difference between librarian and faculty publication behaviors. An odds ratio was also calculated that reveals that librarians are only 1.029 times more likely to self-archive their articles than faculty. Results from the logistic regression model analysis also included information that librarians and faculty have similar behavior with regard to self-archiving the OA version of their publication, and the researchers provide data in table format in order to depict the relationships between predictor variables and dependent variables. With regard to author status and citation counts, faculty have more citation numbers, self-citations are not related to author status, and faculty tend to self-cite more often. Librarians favor co-authorship more than faculty, and faculty articles tend to be lengthier and utilize more references. Effectiveness of the logistic regression analysis was tested using the Hosmer-Lemeshow test for goodness of fit and showed that logistic regression analysis was the proper method for analyzing data collected with a 74.8 success rate. According to the article, there is no difference between librarian and faculty with regard to self-archiving OA activity; faculty members receive more citations regardless of OA status; and there are differences between the two with regard to other variables of articles. Conclusion – Because librarians and LIS faculty are considered to be advocates for self-archiving and are often involved with institutional repositories, it is surprising that they are not themselves participating more in self-archiving behaviors.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,033
score de la tête « metaresearch » (Gemma)0,116
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCommunication savante, Science ouverte
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,998
Score d'incertitude au seuil0,172

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0330,116
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,004
Études des sciences et des technologies0,0020,001
Communication savante0,0050,005
Science ouverte0,0020,005
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0080,001

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.

Tête enseignante Opus0,017
Tête enseignante GPT0,260
Écart entre enseignants0,243 · 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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeObservationnel
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
Publié2012
Routes d'admission1
Résumé présentoui

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