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Record W2787511917 · doi:10.5430/jha.v7n1p35

Analysis of the organizational culture at a hospital in Benin

2018· article· en· W2787511917 on OpenAlexvenueno aff
Ghislain Emmanuel Sopoh, Michael Florian Kouckodila Nzingoula, Charles Sossa, Yolaine Hessou Ahahanzo-Glèlè, Edgard-Marius Dona Ouendo, Laurent Ouédraogo, Michel Makoutodé

Bibliographic record

VenueJournal of Hospital Administration · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsClanOrganizational cultureMultilevel modelTeamworkHealth carePsychologyCohesion (chemistry)NursingConstructivePerceptionGroup cohesivenessDescriptive statisticsFamily medicineMedicineManagementSocial psychologyPublic relationsSociologyPolitical science

Abstract

fetched live from OpenAlex

Objective: To describe the organizational culture (OC) and its strength in a Hospital in Benin.Methods: This is a descriptive cross-sectional study which involved 121 participants (care providers, support and executive staff) of the Lokossa regional hospital in March 2015. Data on dimensions of OC were collected using a questionnaire developed from the Cameron and Quinn’s tools (2006).Results: The mean age of participants was 41 ± 8.3 years and working experience was less or equal to five years in 52.07%. The determined OC was clan-like, hierarchical and results-oriented. This type of OC resulted mainly from cohesion factors, strategic accents, criteria of success, and organizational leadership used by the executive staff. A proportion of 62% (or 75/121) participants had positive perceptions of this OC. However, participants wished more hierarchical and results-oriented OC.Conclusions: The study revealed a mixed OC, positively perceived by workers. This reflects their integration within the organization, adherence to the projects and values of the organization and their involvement in work, allowing a constructive work design. Strengthening the hierarchical orientation and result-based option of the OC may improve the performance of the hospital.

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)0.001
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 score0.009
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.417
Teacher spread0.386 · 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
Published2018
Admission routes1
Has abstractyes

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