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Record W2311247204 · doi:10.1177/0192513x15623588

Who Is in Charge of Family Finances in the Russian Two-Earner Households?

2015· article· en· W2311247204 on OpenAlexaboutno aff
Dilyara Ibragimova, Alya Guseva

Bibliographic record

VenueJournal of Family Issues · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Demographic economicsEconomicsQuarter (Canadian coin)Labour economicsPovertyInequalityWelfarePower (physics)Economic growthGeographyMarket economy

Abstract

fetched live from OpenAlex

Using a recent representative survey and supplemental interviews, we investigate household money management and domestic power dynamics in contemporary Russian two-partner families. During the Soviet period, it was women who typically managed household money. Today, while 45.6% of contemporary Russian two-partner households pool money and manage it jointly, and in about a quarter of families women are in charge, families with men in control of domestic money are on the rise among more affluent spouses who have been married for less than 20 years. While previous work finds evidence for the feminization of poverty in the postcommunist region, we underscore the otherwise hidden aspects of inequality—gendered access to household money among the relative “winners” of the transition: Younger and more affluent families. We place these changes in the context of neoliberal market reforms, including labor market and welfare policy changes and the rise of neoconservative gender ideology.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.083
GPT teacher head0.352
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), 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

Citations43
Published2015
Admission routes1
Has abstractyes

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