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Record W2750811159 · doi:10.7202/1040992ar

ACADEMIC LEADERSHIP IN THE CONTEXT OF NEOLIBERALISM

2017· article· en· W2750811159 on OpenAlexaffvenueabout
Lisa Barnoff, Ken Moffatt, Sarah Todd, Melanie Panitch

Bibliographic record

VenueCanadian social work review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsCarleton UniversityToronto Metropolitan University
Fundersnot available
KeywordsManagerialismPublic relationsAccountabilityAusteritySociologyNegotiationContext (archaeology)Neoliberalism (international relations)Shared leadershipPolitical scienceWork (physics)Leadership stylePoliticsSocial science

Abstract

fetched live from OpenAlex

Driven by neoliberal principles, new managerialist demands for austerity and accountability are reshaping the practices of directors of Canadian schools of social work. In this paper, we discuss research that aimed to clarify how directors of social-justice-oriented social work schools engage in academic leadership in the context of new managerialism. We were especially interested to know how this engagement affects them. Our data come from five interviews and one focus group with five directors of schools of social work in Canada. Four themes emerged from the data: directors’ fight for resources; directors as agents for resource management; directors as ‘buffers’ to shield their faculty from stresses associated with resource cuts; and resistance through relationship-building. Pushed to act as resource managers, directors’ efforts are largely unknown and sometimes unappreciated by faculty members. Our findings will be useful to professional schools negotiating their future in the university system, especially at a time when social work faculties struggle to motivate individuals to take on leadership roles. Overall, the findings of this study help clarify the nature of leadership practices in schools of social work, contributing to a better understanding of the current situation, the requirements of leadership, and how to support leadership.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.288
GPT teacher head0.421
Teacher spread0.133 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2017
Admission routes3
Has abstractyes

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