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Record W2791664819 · doi:10.5430/jnep.v8n8p12

Saudi female university employee self-determination in their own health-related issues

2018· article· en· W2791664819 on OpenAlexvenueno aff
Liisa Elina Hallila, Jehad Omar Al-Halabi

Bibliographic record

VenueJournal of Nursing Education and Practice · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentQualitative researchPsychologyHealth careGender studiesSociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Introduction: To date, there have been no studies located investigating Saudi women's self-determination in their own health-related issues. This study aims to investigate how women in Saudi Arabia see their ability and willingness to decision making in this matter.Methodology: The study design is ethnonursing and Leininger’s Sunrise model was utilized as background theory; qualitative data analysis method was used. 12 Saudi women worked at a large University in Saudi Arabia were interviewed in-depth.Results and discussion: Seven universal Saudi Arabian cultural themes were identified: customs and traditions, women’s decision-making denied, shared decision-making, informed women and empowerment rise, financial status matters, emerging changes in the society, and impact from the Western world.Conclusions: One of the major findings in the interviews was that all research participants observed themselves as more independent and empowered than in the accounts reflecting other women they knew. They saw other women, whom they met at the hospital or who were their friends or relatives, were without equal rights for independent decision making. Mainly, men are interested in reproductive health and are willing to dominate women’s independent decision making in healthcare. The main conclusion, according to this study, the Saudi women research participants who are educated, are more independent in their health-related decision making than the previous literature suggested. The result may be different in villages and among less educated women and their husbands.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.073
GPT teacher head0.431
Teacher spread0.358 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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