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Record W2592132572 · doi:10.18357/ijcyfs81201716740

BAD JOBS, BAD PARENTS? HOW JOB CHARACTERISTICS RELATE TO TIME WITH CHILDREN AND SELF-EVALUATIONS OF PARENTS

2017· article· en· W2592132572 on OpenAlexvenueno aff
Sabrina L. Speights, Samuel J. Grubbs, Beth A. Rubin

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyWorkforcePsychologyWork (physics)Set (abstract data type)Developmental psychologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Using a data set of employed parents in the United States, the <em>2008 National Study of the Changing Workforce</em>, this paper examines work characteristics, the amount of time parents spend with their children, and how parents evaluate themselves in their parenting role (their “self-evaluations as parents”). The results indicate that although work hours correlate with time spent with children, they do not correlate with parents’ self-evaluations. Autonomy is critical to both parenting outcomes, even after controlling for time spent with children. Family structure is also correlated with time spent with children, but not with self-evaluations. These findings indicate that for working parents, some of the characteristics of their work influence both the amount of time spent with children and the degree to which they feel they are good parents.<br /><br /><strong>Authors’ note:</strong> A previous version of this paper was presented at the 2015 Annual Meeting of the Southern Sociological Society in New Orleans, Louisiana.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.023
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.031
GPT teacher head0.321
Teacher spread0.290 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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