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Record W2912877636 · doi:10.33137/cjal-rcbu.v4.29311

Leadership Development for Academic Librarians: Maintaining the Status Quo?

2019· article· en· W2912877636 on OpenAlexvenueno aff
Samantha Hines

Bibliographic record

VenueCanadian Journal of Academic Librarianship · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsStatus quoTransformational leadershipDiversity (politics)Public relationsProfessional developmentValue (mathematics)CurriculumSociologyCritical race theoryPolitical scienceOrder (exchange)Race (biology)Frame (networking)Engineering ethicsPedagogyPsychologyEngineeringBusinessComputer scienceGender studies

Abstract

fetched live from OpenAlex

Leadership development experiences within librarianship are immensely popular. The informal critiques that are leveled at these programs, however, claim that they serve only to reinforce the status quo and that they do not address the real issues affecting our profession, particularly those relating to racial and gender diversity. In order to critically determine the value of these programs, I examine them through the lens of critical race theory. Elements of critical race theory are illustrated through details solicited from the program coordinators and from available information on program websites and in professional literature. While these leadership programs frame themselves as creating transformational leaders, focusing on team-building, collaboration, and motivation, their curriculum and structure perpetuate the status quo in relation to librarianship's existing structural biases. There are steps that can be taken, however, to better develop diverse leaders with our professional values in mind.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.033
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0180.024
Scholarly communication0.0270.018
Open science0.0020.011
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.002

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 head0.136
GPT teacher head0.308
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations10
Published2019
Admission routes1
Has abstractyes

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