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Record W4308440236 · doi:10.1108/oth-07-2022-0037

Moral courage: restoring well-being, community, and capacity within the post-pandemic university

2022· article· en· W4308440236 on OpenAlexaff
Melanie Jeanne Humphreys

Bibliographic record

VenueOn the Horizon The International Journal of Learning Futures · 2022
Typearticle
Languageen
FieldPsychology
TopicLeadership, Courage, and Heroism Studies
Canadian institutionsThe King's University
Fundersnot available
KeywordsCourageFlourishingHumanityValue (mathematics)OriginalityPandemicSociologyMoral couragePublic relationsEngineering ethicsPolitical scienceEnvironmental ethicsCoronavirus disease 2019 (COVID-19)PsychologyLawSocial scienceMedicineSocial psychologyEngineering

Abstract

fetched live from OpenAlex

Purpose This paper aims to spark dialogue regarding what it takes to lead well as a university leader post-pandemic. While much has been written about the future challenges facing universities, not a lot has been written about the kind of moral courage that is required to lead them. There never has been a more important time for strong leadership from university presidents; leadership that supports human flourishing and learning in all its forms. Design/methodology/approach Discussion focuses on the role of presidents in leading the post-pandemic university. The author speaks from experience on the need to restore well-being, community, and capacity for a more hopeful and resilient future. Findings This study makes a case for a post-pandemic university needing to be marked by courage and humanity. Students are looking for universities to align with what they care about and what is relevant to their experience and future. Responsibility falls to leaders within the academy to restore well-being, community and capacity across the university. Research limitations/implications Leading a university as president, at the best of times, is a complex and rewarding role. Leading during a global pandemic could hardly get more challenging. It is hoped that this paper will generate additional discussion as to what it means to lead well in the academy. Originality/value The author’s experience having led a university through one of the most challenging times in our history may provide a perspective for colleagues and future leaders of the university sector.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.279
Teacher spread0.233 · 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 designQualitative
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

Citations2
Published2022
Admission routes1
Has abstractyes

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