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Record W4398291303 · doi:10.7910/dvn/64hpwb

The Effect of Pregnancy on Engagement with Politics. Toward a Model of the Political Consequences of the Earliest Stages of Parenthood

2022· dataset· en· W4398291303 on OpenAlexaff
Elin Naurin, Dietlind Stolle, Elias Markstedt

Bibliographic record

VenueHarvard Dataverse · 2022
Typedataset
Languageen
FieldSocial Sciences
TopicPopulism, Right-Wing Movements
Canadian institutionsMcGill University
Fundersnot available
KeywordsPoliticsPregnancyPolitical scienceGender studiesSociologyBiologyLawGenetics

Abstract

fetched live from OpenAlex

How do pregnancy and childbirth affect engagement in politics and society? Our data from a large-scale citizen panel record political engagement before, during, and after pregnancy for (future) mothers and fathers. We find that women demobilize from politics and societal issues during pregnancy. This disengagement is strongest for indicators of political participation and seeking of political news. Our analysis also shows that gender gaps in political engagement are not only strengthened but also partly created in the earliest stages of parenthood. While the effects are relatively minor, they are robust to various analysis techniques. Some effects also last until the child grows older. Pregnancy and childbirth rarely lead to political mobilization, and when they do, they concern child-related activities, such as attempts to change daycare providers, but only at later stages of early parenthood.

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)0.002
metaresearch head score (Gemma)0.011
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.077
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.008

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 head0.033
GPT teacher head0.296
Teacher spread0.262 · 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
GenreDataset

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

Citations0
Published2022
Admission routes1
Has abstractyes

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