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Record W2341177586 · doi:10.5539/ass.v12n5p147

The Evolution of University Governance in Ghana: Implications for Education Policy and Practice

2016· article· en· W2341177586 on OpenAlexvenueno aff
Bernard Bekuni Boawei Bingab, Joseph Ato Forson, Oscar S. Mmbali, Theresa Yaaba Baah-Ennumh

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governancePublic administrationPolitical scienceAccountingBusinessEconomicsManagement

Abstract

fetched live from OpenAlex

<p>The relationship between education and public policy is two way: (1) economic development of a nation depends on the human capital produced by the education system of that nation and (2) public spending and management of the education system is crucial to the welfare of the nation. Changes in this relationship generate public concerns about university governance and its implications to national development. Therefore, this study explores the questions: (1) Have the role and purpose of university governance changed since its inception? (2) Are there differences between the old and the new system of university governance? (3) What larger ramifications does this have on university governance? The study was conducted within the framework of qualitative research design. The researchers adopted the social constructivist worldview with phenomenology approach to inquiry. Participants who were mainly eminent former senior university administrators and regulators with management, administrative and governance experience in public and private university were interviewed. Data was transcribed and read repeatedly over time to make sense of issues raised by informants. Significant statements were selected, interpreted and used in the text to highlight key issues as well as to provide voice of the informants. The findings of the study suggest that remedies for the changes realized in governance should take into account measures such as strengthening institutional capacities; balancing between the interests of the private and public sector actors in university education; and safeguarding the policy space of the ordinary people to participate in university education affairs that concern or affect them. </p>

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.977
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.348
Teacher spread0.334 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations5
Published2016
Admission routes1
Has abstractyes

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