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Record W2774470953 · doi:10.5539/ijps.v9n4p109

Reasons and Ramifications of Tardy Marriages among Educated Muslim Women Folk in Indian Controlled Kashmir: An Introspection from Social Psychology Standpoint

2017· article· en· W2774470953 on OpenAlexvenueno aff
Suriya Hamid

Bibliographic record

VenueInternational Journal of Psychological Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsIntrospectionPsychologyVirtueSocial psychologySociologyGender studiesLawPolitical science

Abstract

fetched live from OpenAlex

Since times immemorial, marriage is considered as an act by virtue of which two individuals make their relationship manifest in terms of a bond that putatively lasts for life time. Spiritually, marriages are believed to be settled in heavens and solemnized on earth. This metaphoric scenario is often practiced other way round in the valley of Kashmir. As a matter of fact, the process of seeking a life associate and its consolidation in terms of marriage is so cumbersome and unenviable that it often leads the women folk of Kashmir into cyclic rethinking about its eudaemonia. In the anticipation of endorsements for a happy married life with the tendency of zeroing risk factors, the dingy psycho-evolved system that is dominant now-a-days leads the Kashmir phratry towards the manifestation of tardy marriages. This piece of research work aims to ascertain the reasons and axiomatic ramifications that lead to tardy marriages among educated Muslim Women folk in Kashmir Valley. This study is also an attempt to comprehend the social stratification and cultural dynamics of Kashmir as is introspected from social psychology standpoint. This paper unfolds the coalescing systematics of major issues and complexities of tardy marriages in order to present a strategic arduous solution to counter and castigate this imperil that creates distortion and soreness in the social fabric of Kashmir.

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)0.002
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 score0.217
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.457
Teacher spread0.381 · 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
Published2017
Admission routes1
Has abstractyes

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