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Record W2404515890 · doi:10.5539/gjhs.v9n1p102

Investigating the Relationship between Body Management and Modern Identity among Married Women in Tehran City

2016· article· en· W2404515890 on OpenAlexvenueno aff
Hassan Rafiey, Mohammad-Ali Mohammadi, Mohammad-Bagher Alizadeh Aghdam, Saeed soltani Bahram

Bibliographic record

VenueGlobal Journal of Health Science · 2016
Typearticle
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Cluster samplingVariance (accounting)Consumption (sociology)PsychologyIdentity managementDemographySociologyGeographySocial scienceBusinessAesthetics

Abstract

fetched live from OpenAlex

INTRODUCTION: One of the characteristics of the modern age is to pay attention to visual symbols. In recent periods, body had found basic importance because of being the most available instrument to exhibit the identity forms and had been transformed to an identity media.METHODS: In this cross-sectional survey, the relationship between body management and modern identity has been studied on 400 married women in Tehran city. The sampling method used in this research is multistage cluster sampling.RESULTS: In the range of 50 to 87, the mean score of body management was 66.18 that indicates a body management behavior around average among participants. A positive, significant relationship (r=0.32) between modern identity and body management was found. Regression analysis showed that modern identity, monthly family income, educational level, and age can explain 20% of the variance of body management.CONCLUSION: It may be concluded that the higher the level of modern identity, the higher the level of body management will be. Based on Giddens’ theory, it can be stated that in the consumption world, the women according to their tastes and interests are trying to present themselves beautiful and youthful and to make a distinguished personal identity of themselves. Therefore, the body style and statues are some of the mechanisms that the women used to reveal their identity.

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)0.005
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 score0.057
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.076
GPT teacher head0.386
Teacher spread0.310 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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