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Record W2742873291 · doi:10.5539/hes.v7n3p132

Quality Management in Higher Education: Review and Perspectives

2017· article· en· W2742873291 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHigher Education Studies · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Leadership and Management Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsHigher educationEnthusiasmTransformational leadershipQuality (philosophy)ConstructivePublic relationsPsychologySociologyPolitical scienceComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

This paper is a review which presents a summary of 52 studies from 2006 to 2016 in Quality Management (QM) within Higher Education Institutes (HEIs). The aim of this paper is to submit evidence regarding the level of QM in HEIs, particularly in developing countries, and also to enhance the research in the field of QM. The findings reveal that from 2013 onward there is an increased interest in the items of QM mainly in Arabic countries. Moreover, the findings include Critical Success Factors (CSFs), obstacles and benefits that confirm and supplement previous literature. The type (private or public) and age of university, transformational leadership, integration, respect of a person, character, constructive conflict, creative tension, enthusiasm, awareness and orientation of employees and faculty and resource allocation are CSFs that this study reveals. Also, infrastructure limitations focused on human and financial capital, limited involvement of stakeholders and measurement of a complex range of performance indicators are barriers which enrich the analysis. Moreover, the extra benefits of QM practices are that QM is appropriate to the purpose of HEIs, meets the expectations and the new roles of HEIs, and lastly, the implementation of QM practices can solve problems and propose solutions.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.887
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.179
GPT teacher head0.390
Teacher spread0.211 · 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