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Enregistrement W2724373517 · doi:10.18438/b8ss97

AAU Library Directors Prefer Collaborative Decision Making with Senior Administrative Team Members

2017· article· en· W2724373517 sur OpenAlexvenueaboutno aff
Carol Perryman

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2017
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueLibrary Science and Information Literacy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSalarySuccession planningStrategic planningPsychologyEthnic groupPublic relationsSenior managementMedical educationPolitical scienceLibrary scienceManagementBusinessMarketingMedicineComputer science

Résumé

récupéré en direct d'OpenAlex

A Review of: Meier, J. J. (2016). The future of academic libraries: Conversations with today’s leaders about tomorrow. Portal: Libraries and the Academy, 16(2), 263-288. Retrieved from http://muse.jhu.edu/article/613842 Abstract Objective – To understand academic library leaders’ decision making methods, priorities, and support of succession planning, as well as to understand the nature, extent, and drivers of organizational change. Design – Survey and interview. Setting – Academic libraries with membership in the Association of American Universities (AAU) in the United States of America and Canada. Subjects – 62 top administrators of AAU academic libraries. Methods – Content analysis performed to identify most frequent responses. An initial survey written to align with the Association of Research Libraries (ARL) 2014-2015 salary survey was distributed prior to or during structured in-person interviews to gather information about gender, race/ethnicity, age, time since terminal degree, time in position, temporary or permanent status, and current job title. 7-question interview guides asked about decision processes, strategic goals, perceived impacts of strategic plan and vision, planned changes within the next 3-5 years, use of mentors for organizational change, and succession planning activities. Transcripts were analyzed to identify themes, beginning with a preliminary set of codes that were expanded during analysis to provide clarification. Main results – 44 top academic library administrators of the 62 contacted (71% response rate) responded to the survey and interview. Compared to the 2010 ARL Survey, respondents were slightly more likely to be female (55%; ARL: 58%) and non-white (5%; ARL: 11%). Approximately 66% of both were aged 60 and older, while slightly fewer were 50-59 (27% compared to 31% for ARL), and almost none were aged 40-49 compared to 7% for the ARL survey. Years of experience averaged 33, slightly less than the reported ARL average of 35. Requested on the survey, but not reported, were time since terminal degree and in position, temporary or permanent status, and current job title. Hypothesis 1, that most library leaders base decisions on budget concerns rather than upon library and external administration strategic planning, was refuted. Hypothesis 2, that changes to the academic structure are incremental rather than global (e.g., alterations to job titles and responsibilities), was supported by responses. Major organizational changes in the next three to five years were predicted, led by role changes, addition of new positions, and unit consolidation. Most participants agreed that while there are sufficient personnel to replace top level library administrators, there will be a crisis for mid-level positions as retirements occur. A priority focus emerging from interview responses was preparing for next-generation administrators. There was disagreement among respondents about whether a crisis exists in the availability of new leaders to replace those who are retiring. Conclusion – Decisions are primarily made in collaboration with senior leadership teams, and based on strategic planning and goals as well as university strategic plans in order to effect incremental change as opposed to wholesale structural change.

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)0,001
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, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCommunication savante
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,930
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0030,001
Communication savante0,0060,854
Science ouverte0,0010,000
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 Opus0,022
Tête enseignante GPT0,333
Écart entre enseignants0,311 · 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

Citations1
Publié2017
Routes d'admission2
Résumé présentoui

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