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Record W2029933423 · doi:10.5539/ibr.v4n2p153

Measuring the Effect of Academic Satisfaction on Multi-Dimensional Commitment: A Case Study of Applied Science Private University in Jordan

2011· article· en· W2029933423 on OpenAlexvenueno aff
Ali Faleh, H. Aborumman As'ad

Bibliographic record

VenueInternational Business Research · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsSalaryTeamworkIncentivePsychologyStratified samplingTest (biology)Job satisfactionPopulationContinuanceMedical educationSocial psychologyMarketingManagementPolitical scienceSociologyBusinessMedicineStatisticsDemographyMathematicsEconomics

Abstract

fetched live from OpenAlex

The purpose of this study was to empirically test whether academic satisfaction (university vision, respect and recognition, relationship with colleagues, teamwork, incentives, management support, salary) has an effect on university commitment (affective, normative, continuance), The population comprised of academic staff in Applied Science Private University, a questionnaire survey was adopted to collect the primary data from the respondents whom they were randomly selected using a stratified sampling technique, a total of 300 questionnaires were administered to potential respondents from the 9 faculties.The study findings indicate that overall academic satisfaction has a statistical significant effect on overall university commitment, it also reveals that university vision, teamwork, management support, salary and work environment has more impact on overall university commitment than respect and recognition, relationship with colleagues and incentives.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.153
GPT teacher head0.394
Teacher spread0.241 · 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

Citations13
Published2011
Admission routes1
Has abstractyes

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