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Enregistrement W1582814552 · doi:10.18438/b81c98

Retention Initiatives are Employed in Academic Libraries, Although not Necessarily for this Purpose

2011· article· en· W1582814552 sur OpenAlexaffvenue
Laura Newton Miller

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2011
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueLibrary Science and Information Literacy
Établissements canadiensCarleton University
Organismes subventionnairesnon disponible
Mots-clésLibrary sciencePsychologyTable of contentsMedical educationMedicineComputer scienceWorld Wide Web

Résumé

récupéré en direct d'OpenAlex

Objective – To study methods that support retention of academic librarians.
 
 Design – Exploratory research using an online survey; non-random sample.
 
 Setting – Academic libraries, nearly all located within the U.S. (97.2%). 
 
 Subjects – A total of 895 professional academic librarians.
 
 Methods – The researchers sent an online survey link to professional electronic mail lists and directly to heads of Association of Research Libraries (ARL) member libraries. The 23-item survey was available from February 19, 2007, through March 9, 2007, and contained questions about the professional experience of respondents, their libraries, and their universities. Subjects were asked to identify retention activities that were currently offered at their workplaces (both library-specific and university-wide) and to rate their satisfaction for each available initiative. The list contained fifteen initiatives based on the researchers’ literature review.
 
 Main Results – Almost half (46.3%) of respondents were 50 or older and 7.5% under 30 years old, leaving 46.2% between the ages of 30-50 years old (although this percentage is not explicitly stated in the paper except in a table). Nearly half of the subjects were in the first ten years of their careers. 80.2% had held between one and four professional positions in their careers, and even when length of professional experience was factored out, age had no effect on the number of positions held. Most job turnover within the past three years (3 or fewer open positions) was in public service, while other areas of the library (i.e., technical services, systems, and administration) reported zero open positions. Only 11.3% of respondents noted that their libraries have deliberate, formal retention programs in place. Despite this, there are several library- and university-based initiatives that can be considered to help with retention. The most reported available library-based retention initiative was the provision of funding to attend conferences (86.8%). Librarians also frequently reported flexible schedules, support and funding for professional development and access to leadership programs. University-based retention programs included continuing education funding, new employee orientations, faculty status, and the chance to teach credit-bearing courses. Only 22.2% of subjects reported formal mentoring programs as a retention strategy. Librarians were very or somewhat satisfied with schedule flexibility (79.6%). They were generally satisfied with other initiatives reported. In response to 22 five-point Likert scale descriptions of positive library work environments, subjects most agreed with statements that allowed librarians to have control of their professional duties, that allowed for personal or family obligations, and that supported professional development. Librarians agreed less often regarding statements about salaries, research support, and opportunities for advancement.
 
 Conclusion – Academic librarians are involved in and are benefitting from some library and university-based retention initiatives, even though retention may not be the primary strategic goal.

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)0,002
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCommunication savante
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,954
Score d'incertitude au seuil0,799

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,004
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 savante0,0010,820
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,083
Tête enseignante GPT0,328
Écart entre enseignants0,246 · 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 tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

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
Publié2011
Routes d'admission2
Résumé présentoui

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