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Record W2065754603 · doi:10.1080/15544770802367770

Equal Participation but Separate Paths?: Women's Social Capital and Turnout

2009· article· en· W2065754603 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Women Politics & Policy · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsQueen's University
Fundersnot available
KeywordsTurnoutSocial capitalVotingReciprocity (cultural anthropology)Political capitalPolitical scienceDemographic economicsPoliticsSocial mobilitySurvey data collectionSociologySocial psychologyEconomicsPsychologyLaw

Abstract

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Abstract Conventional models of voter turnout lead us to expect men to vote in greater numbers than women. Yet in advanced industrialized democracies, women tend to participate in elections as much, or more, than men do. This study addresses this puzzle by drawing on the social capital literature to help explain the paradox of voter turnout for women. Women are in fact “rich” in various forms of social capital, especially more informal networks of reciprocity which are often viewed as apolitical and not measured in resource models of voter turnout. Drawing on the Canadian National Survey of Giving, Volunteering, and Participating (NSGVP), the findings show that informal social capital helps explain why women turn out to vote at similar levels as men, despite having fewer traditional resources at their disposal. Hence, this study provides evidence that women's path to participation is different than men's. The author would like to thank Jillian Evans who provided helpful feedback on earlier drafts of this article. Keywords: voter turnoutgender gapsocial capitalreciprocitysocio‐economic resourcesCanada Notes The author would like to thank Jillian Evans who provided helpful feedback on earlier drafts of this article. 1. Clearly, there is variation among women with respect to their access to resources. Ethnic background, marital status, and immigrant status structure women's access to resources as well. 2. While voting is certainly a form of political participation, the act of voting does differ in some respects from other forms of political participation because of the relative small amount of time and civic skills required to carry out the act, and its egalitarian quality (i.e. that everyone has a right to vote and that more motivated individuals can not vote more than once). For a discussion of these differences, see Verba, Schlozman, and Brady (2001, 23–24). 3. This effectively creates a sample of respondents who were at least 18 years old at the time of interview. 4. The working weight was the population weight divided by the mean of the population weight. 5. Not surprisingly, reported turnout is higher than the actual turnout of 67 percent reported by Statistics Canada for the 1997 election. Official data is not available by gender. 6. This finding holds if the three activities that create this measure are examined individually as well, i.e. men were significantly more likely to be a member of a political party, a labor and/or professional association, and a service club and/or fraternal organization (p<.01). 7. Across the five types of activities included in the measure, women are significantly more likely to canvas, campaign or fundraise for a cause, and help organize or supervise activities for a group. There are no significant differences on the other three items. 8. Along with gender, racial and ethnic background may also impact how social capital is translated into political participation. Unfortunately, no variable is available for ethnic background in the NSGVP. However, there is evidence that informal social capital is important to women across other cleavages that shape women's experiences. When the model in Table 4 is run separately for immigrant women, the results are similar to the full sample model for women, suggesting that the importance of social capital variables is similar across sub‐groups of women (results not shown). 9. The CLARIFY program is used to conduct the simulations, as developed by King, Tomz, and Wittenberg (Citation2000). 10. For detailed work on the impact of social networks for communicating political information, see Huckfeldt and Sprague (Citation1995).

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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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.365
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.340
Teacher spread0.322 · 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