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Enregistrement W4221127908 · doi:10.18438/eblip29971

Supporting the Intersections of Life and Work: Retaining and Motivating Academic Librarians Throughout Their Careers

2022· article· en· W4221127908 sur OpenAlexvenueno aff
Lori Birrell, Marcy A. Strong

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2022
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueLibrary Science and Information Literacy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésKaleidoscopeFeelingPsychologyConversationDocumentationCoding (social sciences)Medical educationComputer scienceSocial psychologyMedicineSociology

Résumé

récupéré en direct d'OpenAlex

Objective – This study uses the Kaleidoscope Career Model (Mainiero & Sullivan 2006a) to determine key sources of motivation for library professionals during their careers and identifies strategies for how library administrators can better retain and inspire their staff. Methods – The authors adapted the Kaleidoscope Career Model survey tool with permission from Mainiero and Sullivan. The authors used Qualtrics to send out the adapted survey and in October 2019 emailed a call for participation with the survey link to six library electronic mailing lists. A total of 433 participants completed the survey. The authors reviewed the demographic data and charts Qualtrics generated and used an open-coding method to analyze the qualitative responses to open-ended questions included in the survey. First, they read through those responses, identified common words, phrases, and ideas, which became initial codes. Then the authors reviewed the codes and determined themes common in the data. Each author coded and analyzed each question. Those themes then informed the discussion and recommendations shared in this article. Results – Nearly 60% of respondents identified as being in the Authenticity phase, 15% in the Challenge phase, and 18% in the Balance phase. When asked if they felt supported, those in the Authenticity phase reported the highest overall level of satisfaction, with those in the 47–52 years old cohort experiencing peak feelings of support. The study found that all early career practitioners seemed interested in continuing in a supervisory role. Those older participants in the Balance phase were less interested than those in the other two phases in continuing to supervise. Those in the Authenticity phase identified most strongly with being organizational leaders. By contrast, older participants in the Balance phase did not identify strongly as leaders. Those in the Challenge phase showed strong interest in being leaders at an early age and that interest increased among older cohorts. Conclusion – This study is the first to analyze sources of motivation for academic librarians during the stages of their careers. When working with librarians who identify with the Authenticity phase, administrators should work with their employees to develop career goals that are extrinsically based, such as what can be achieved through good work rather than striving for a dream position. Librarians in the Balance phase would benefit from early opportunities to develop leadership roles or serve in supervisory roles. These early opportunities better fit with their efforts to prioritize family later in life. Librarians in the Challenge phase are intrinsically motivated to achieve and strive. They may experience disappointment as newer career librarians continue to advance and as they begin to plateau later in life. Leaders must consider the kinds of changes their organization can withstand as they strive to best support and foster the growth and development of all of their employees.

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)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies, Communication savante
Catégories consensuellesaucune
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 enseignants0,651
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,000
Communication savante0,0010,407
Science ouverte0,0000,000
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 Opus0,031
Tête enseignante GPT0,309
Écart entre enseignants0,278 · 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
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

Citations3
Publié2022
Routes d'admission1
Résumé présentoui

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