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Record W2602581495 · doi:10.3138/jcfs.40.1.97

Attitudes toward Family Size Preferences in Urban Ethiopia

2009· article· en· W2602581495 on OpenAlexaffvenue
Daniel Telake Sahleyesus, Roderic Beaujot, David Zakus

Bibliographic record

VenueJournal of Comparative Family Studies · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsWestern UniversityToronto Public HealthCentre for Global Health Research
Fundersnot available
KeywordsChildlessnessFertilitySocial capitalRealmHuman capitalFocus groupValue (mathematics)Demographic economicsPsychologySocial psychologyPopulationSociologyEconomic growthGeographyDemographyEconomicsSocial science

Abstract

fetched live from OpenAlex

Making use of data obtained from fieldwork conducted in five major urban centers of Ethiopia in the summer of 2004, this study examines the attitudes of respondents on family size preferences to understand the fertility transition in urban areas. The methodology includes in-depth qualitative interviews and focus group discussions. The findings suggest that children continue to have an immeasurable value for urban residents. However, people differ in their preferences towards family size. A family of four or more children is defined as large by the majority of participants of the study and about three-quarters of them disapproved of large family sizes. The findings show that voluntary childlessness is not within the realm of choice. The overwhelming majority of participants were in favor of small families rather than opting for childlessness. Urban residents have a reproductive goal that takes into account reducing costs in the face of economic hardships and tailoring preferences to achieve upward social mobility. There is emphasis on the wellbeing of relatively smaller number of children and attaining a certain level of investment in one’s own human capital which are incompatible with large family size preferences.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.219
GPT teacher head0.427
Teacher spread0.208 · 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

Citations7
Published2009
Admission routes2
Has abstractyes

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