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Record W4393007079 · doi:10.1051/shsconf/202418704015

ICT Governance in Higher Education: A Case Study of a Vocational College in Libya

2024· article· en· W4393007079 on OpenAlexaff
Ali Etkkali, Poba-Nzou Placide

Bibliographic record

VenueSHS Web of Conferences · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInformation Systems Theories and Implementation
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsInformation and Communications TechnologyArchetypeVocational educationCorporate governanceContext (archaeology)Higher educationPublic relationsPolitical scienceSociologyBusinessKnowledge managementPedagogyManagementEconomicsComputer science

Abstract

fetched live from OpenAlex

This study focuses on ICT governance in higher education in a developing country. The research employs an interpretive single case study to describe and understand ICT governance at Alpha, a vocational computer college in Libya. Fourteen key informants, including deans, teachers, and students, participated in the interviews. Consistent with previous studies, our results reveal formal ICT governance arrangements at Alpha College. However, Alpha College leverages its general management structure and processes to make ICT decisions and fulfill the needs of the college stakeholders. In addition, the structure supporting ICT decision-making at Alpha College qualifies as “Centralized” while the ICT archetype of “Business Monarchy” best describes its ICT governance arrangements. Surprisingly, our study also reveals the hybridization of the role of the Dean through the integration of “entrepreneurial activities” amid his efforts to fulfill the ICT needs of the college in the context of severe budget constraints.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0150.004
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.062
GPT teacher head0.381
Teacher spread0.319 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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