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Record W4323074646 · doi:10.4000/monderusse.13939

Constructing the average worker’s family budget after Stalin

2023· article· en· W4323074646 on OpenAlexaff
Kristy Ironside

Bibliographic record

VenueCahiers du monde russe · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsMcGill University
Fundersnot available
KeywordsPledgeNormativePopulationGovernment (linguistics)Power (physics)EarningsSubsidyState (computer science)Political scienceWelfareSociologyEconomicsPublic administrationPolitical economyLawAccountingDemography

Abstract

fetched live from OpenAlex

The article looks at published “average” family budget studies in the Khrushchev era following the February 1956 Twentieth Party Congress and the Soviet government’s pledge to more fully meet the population’s material needs. Despite being portrayed as objective reflections of reality, harnessing the expert authority of statisticians and the power of numbers, as this article shows, these studies in fact featured highly idealized constructions of family composition and economic practices, as well as gendered assumptions about men’s and women’s contributions to the normative household budget. At the same time, published “average” family budget studies played an important pedagogical role during this time, helping to explain the benefits of shifts away from Stalin-era policies, such as encouraging Stakhanovite overproduction and bestowing routine retail price cuts on the population, and toward more abstract but, as it was argued, more tangibly beneficial policies like workers’ “invisible earnings” from the free or highly subsidized benefits of the Soviet welfare state.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.032
GPT teacher head0.233
Teacher spread0.201 · 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.

Study designNot applicable
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
Published2023
Admission routes1
Has abstractyes

Explore more

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