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Record W3112076356 · doi:10.5703/1288284317188

Great Expectations: Leading Libraries Through the Minefield of Continuous Change

2020· article· en· W3112076356 on OpenAlexaff
Denise Novak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicLeadership and Management in Organizations
Canadian institutionsPurdue Pharma (Canada)
Fundersnot available
KeywordsPublic relationsHospitalityManagementFlexibility (engineering)AccountabilityAdministration (probate law)Key (lock)Space (punctuation)Change management (ITSM)SociologyBusinessPolitical scienceMarketingComputer scienceTourismLaw

Abstract

fetched live from OpenAlex

If there is one thing all library administrators and managers can be sure of, it is that our space, our collections, our systems and our leadership will be impacted by change. Managing that change is critical if managers, directors, deans in our libraries will be able to continue to meet the needs of our communities with different tools and resources. This lively discussion will feature brief presentations about how libraries at Carnegie Mellon University and at Kresge Business Administration Library (University of Michigan) have changed in recent history. The presenters will include what worked well and what worked not as well at the two institutions. They will focus on two areas. First, Denise Novak will explore change through five key aspects: nature, process, role, culture and staff participation of change. Second, Corey Seeman will explore change as defined by six key terms: inevitability, rapidity, flexibility, hospitality, accountability, and empathy. Participants at the meeting will be invited to share how change is managed at their institutions and what issues might be present or on the horizon.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
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 head0.091
GPT teacher head0.239
Teacher spread0.148 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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