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Enregistrement W2595592080

Information in Transition : Examining the Information Behaviour of Academics as they Transition into University Careers

2016· dissertation· en· W2595592080 sur OpenAlexfundaboutno aff
Rebekah Willson

Notice bibliographique

RevueStrathprints: The University of Strathclyde institutional repository (University of Strathclyde) · 2016
Typedissertation
Langueen
DomaineSocial Sciences
ThématiqueLibrary Science and Information Literacy
Établissements canadiensnon disponible
Organismes subventionnairesSocial Sciences and Humanities Research Council of CanadaCharles Sturt University
Mots-clésTransition (genetics)Grounded theoryCritical discourse analysisSociologyPedagogyPublic relationsSocial sciencePolitical scienceQualitative research
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Transitions are often times of upheaval. A transition, even when positive, may be disruptive as familiar contexts, supports, and resources change. While early career academics are highly trained and experienced, the transition from doctoral student to academic involves a series of new roles and responsibilities within a new information environment, an environment that has been influenced by neoliberal ideals and become increasingly corporatised and managerial in nature. Within information behaviour research there has been a lack of research that focuses specifically on periods of transition, particularly on individuals in transition over time. Additionally, while there is information behaviour research on academics, it does not address the experiences of academics as they start their careers. This research addresses those gaps. This research used constructivist grounded theory and critical discourse analysis as methodologies to explore the information behaviour of 20 individuals transitioning from doctoral students to academics in Australia and Canada. Academics in the humanities and social sciences, who had recently moved from full-time doctoral studies to full-time academic positions, were followed for a period of between five and seven months. To triangulate the data, three data sources were used: two in-depth interviews, multiple check-ins, and documents. Interviews were analysed using grounded theory analysis, documents using critical discourse analysis. Two theoretical frameworks were used to provide analytical lenses: neoliberalism and Transitions Theory. Several major themes emerged from this research that contribute to both information behaviour research and Transitions Theory. In looking at academics’ work, the number and variety of administrative and managerial tasks universities require academics to perform greatly increases their information needs. Administrative work becomes a layer over all academic work. However, universities frequently fail to provide the information academics require, leaving information needs unfulfilled. Because of this, early career academics frequently seek information from their more senior colleagues, rather than relying on textual sources. Senior colleagues provide timely, convenient, and comprehensive information. Physical proximity and the building of collegial relationships promote information sharing, informal information exchanges, and serendipitous information finding that is of great use to early career academics. Social information is instrumental for early career academics’ settling in to their new positions, as doctoral studies often fail to provide an accurate picture of academic life or to fully prepare students for research, teaching, service, and administrative roles. Comparing and contrasting previous experiences to their current experience is one way that early career academics use new information to learn new ways of working and develop a sense of belonging in academia. From these findings, the theory of Systemic Managerial Constraints (SMC) emerged. SMC views the managerialism that results from neoliberalism within universities as pervasive and constraining both what work early career academics do and how they do it. However, colleagues help to ameliorate the effects of SMC and early career academics learn, as they transition, to enact their personal agency to enable them to do the work that they value.

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)0,006
score de la tête « metaresearch » (Gemma)0,022
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,030
Score d'incertitude au seuil0,059

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,022
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0040,003
Communication savante0,0060,004
Science ouverte0,0010,004
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,011
Tête enseignante GPT0,215
Écart entre enseignants0,204 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
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

Citations8
Publié2016
Routes d'admission2
Résumé présentoui

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