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Record W2105633752 · doi:10.5267/j.msl.2012.09.019

A study on the effect of social capital on learning organization: A case study of Jihad Agriculture Organization of Kermanshah, Iran

2012· article· en· W2105633752 on OpenAlexvenueno aff
Akbar Veismoradi, Peyman Akbari, Reza Rostami

Bibliographic record

VenueManagement Science Letters · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaStatistical populationSocial capitalAgricultureOrganizational learningLearning organizationSample (material)PsychologySocial organizationPopulationDescriptive statisticsBusinessSocial psychologySocial scienceManagementSociologyStatisticsEconomicsGeographyMathematicsDemography

Abstract

fetched live from OpenAlex

One of the challenges in contemporary zone of management and organizational behavior is to create and strengthen social capital. Social capital arises from individuals trying to help people build trust, relationships and cooperation. Without social capital, employees are not able to share information and knowledge. The purpose of this study is to review the relationship of social capital and the learning organizational in one of Iranian organizations called Jihad Agriculture Organization of Kermanshah. The statistical population includes 270 employees of this organization and a sample size of 159 people are chosen using Morgan statistical table for a the first six months of 2012. The research method is descriptive-survey, the type of correlation and a questionnaire for collecting information are used. A number of university professors confirmed validity of the questionnaires. Their reliabilities were obtained with Cronbach's alpha and the coefficients for questionnaire of social capital was 0.705 and for questionnaire of learning organization was 0.838, respectively. By using correlation coefficient and multiple regressions, the data were analyzed. Results in a significant level of 95% showed, social capital had a meaningful relationship with learning organizational.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.123
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.227
Teacher spread0.211 · 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 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

Citations1
Published2012
Admission routes1
Has abstractyes

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