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Record W2517216788 · doi:10.5539/ies.v9n9p133

The Impediments Facing Community Engagement in Omani Educational Tertiary Institutions

2016· article· en· W2517216788 on OpenAlexvenueno aff
Jinan Hatem Issa

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsProsperitySocial capitalThematic analysisHigher educationQualitative researchInstitutionTertiary institutionPolitical scienceCapital (architecture)Capital cityEconomic growthPedagogyPublic relationsSociologyMedical educationSocial scienceGeographyMedicine

Abstract

fetched live from OpenAlex

Prior to the vital role that social capital plays in accomplishing prosperity for any educational tertiary institution, it was emphasised in several countries’ agendas, including the Sultanate of Oman. This study endeavours to explore the impediments facing the enhancement of the social capital in Omani educational tertiary institutions through the lens of community engagement. A case study method employing a purely qualitative approach was employed at one of the six public Colleges of Applied Sciences in Oman. Twelve academicians were purposively semi-structured interviewed. Performing the thematic analysis technique, the results revealed more than ten key impediments. Some implications to stakeholders were illustrated and several suggestions were provided for better performances in terms of this specific capital.

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)0.014
metaresearch head score (Gemma)0.028
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 score0.020
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0200.008
Scholarly communication0.0120.004
Open science0.0020.019
Research integrity0.0030.003
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 head0.192
GPT teacher head0.480
Teacher spread0.288 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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