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Record W4288425328 · doi:10.5539/ies.v15n4p125

The Degree of Jordanian Universities’ Organizational Agility

2022· article· en· W4288425328 on OpenAlexvenueno aff
Amal Ribhi Qtairi, Yazid Isa Alshoraty

Bibliographic record

VenueInternational Education Studies · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCollaboration in agile enterprises
Canadian institutionsnot available
Fundersnot available
KeywordsGraduation (instrument)PsychologyDegree (music)Higher educationSample (material)Degree programPublic universityMedical educationMathematics educationPedagogyPolitical scienceMathematicsPublic administration

Abstract

fetched live from OpenAlex

The study aimed at exploring the degree of Jordanian universities’ organizational agility and its relation to some variables. The correlational descriptive method was applied. The study sample consisted of (369) faculty members working at three public universities representing the three regions of Jordan: (Yarmouk University/The Northern Region), (The Hashemite University/The Central Region), and (Mutah University/The Southern Region). The study results revealed that the degree of organizational agility at Jordanian universities was moderate, and that there were no statistically significant differences in the degree due to sex, experience, and academic rank, but there were statistically significant differences in that degree due to (country of graduation), in favor of the faculty members who graduated from universities in Arab countries,and due to (university), in favor of The Hashemite University faculty members.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.304
Teacher spread0.262 · 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 designObservational
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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