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Record W2146332161 · doi:10.1177/0192513x13506002

Families by Choice and the Management of Low Income Through Social Supports

2013· article· en· W2146332161 on OpenAlexaff
Amber Gazso, Susan A. McDaniel

Bibliographic record

VenueJournal of Family Issues · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsUniversity of LethbridgeYork University
Fundersnot available
KeywordsLate modernitySociologyPerspective (graphical)Face (sociological concept)Life course approachFamily lifeQualitative researchConventionSocial psychologyPsychologyGender studiesSocial science

Abstract

fetched live from OpenAlex

Processes of individualization have transformed families in late modernity. Although families may be more opportunistically created, they still face challenges of economic insecurity. In this article, we explore through in-depth qualitative interviews how families by choice manage low income through the instrumental and expressive supports that they give and receive. Two central themes organize our analysis: “defining/doing family” and “generationing.” Coupling the individualization thesis with a life course perspective, we find that families by choice, which can include both kin and nonkin relations, are created as a result of shared life events and daily needs. Families by choice are then sustained through intergenerational practices and relations. Importantly, we add to the growing body of literature that illustrates that both innovation and convention characterize contemporary family life for low-income people.

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)0.004
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.012
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.338
Teacher spread0.318 · 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

Citations31
Published2013
Admission routes1
Has abstractyes

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