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Record W1678151434

Analytical Study of the Causal Factors of Divorce in African Homes

2015· article· en· W1678151434 on OpenAlexaboutno aff
Adetayo Olaniyi Adeniran

Bibliographic record

VenueResearch on humanities and social sciences · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyFace (sociological concept)Quarter (Canadian coin)Demographic economicsIgnoranceUnemploymentPsychologyDemographySociologyPolitical scienceEconomic growthGeographyEconomics
DOInot available

Abstract

fetched live from OpenAlex

The increasing rate of divorce in African homes is an intricate incident happening among African couples and in the world at large. Family is indeed the bedrock of any continent, and world. The rampant occurrence of divorce in African homes is found to have socio-economic and political effect in the society. Primary data were collected through questionnaires (face-to-face and online) countries across the continent and all were analyzed. The data comprises of sixty married homes, and forty divorcees, consisting of sixty married couples living together, twenty men divorcees and twenty women divorcees were selected at random and given copies of questionnaires. The results showed that respondents perceived barrenness or infertility as the major cause of divorce. It is also followed by other causes such as absence of love, ignorance, poverty, religion differences, unemployment, and others. Marriage counselors were encouraged to carry out more studies in this area in other to find a lasting solution to divorce, effect zero tolerance to divorce in the African homes, and device a means of uniting the divorcees so that Africa as a continent will be emulated and set as a standard for other continents to evaluate their marriage performance. Keywords: causes, divorce, Africa, homes

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
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 head0.559
GPT teacher head0.488
Teacher spread0.071 · 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; both teacher heads agree on what is shown here.

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

Citations16
Published2015
Admission routes1
Has abstractyes

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