The Representation of Women

Santos, Pedro A. G. dos; Wylie, Kristin N.

doi:10.4324/9781315543871-4

Cited by 3 publications

(3 citation statements)

References 1 publication

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“…Second, we included the tree in the imputation and ran PI as well as ML and DL, for which the phylogenetic information was provided through phylogenetic eigenvectors (Diniz-Filho et al (1998); Penone et al (2014)). We performed the eigenvector decomposition using the PVR 0.3 package (Santos, 2018) and included a number of eigenvectors capturing 95% of the tree variance. Third, we combined PI with ML in a two-step approach where the dataset was augmented with the output of a first phylogenetic imputation prior to ML and DL imputation.…”

Section: Imputation Strategiesmentioning

confidence: 99%

Benchmarking imputation methods for discrete biological data

Gendre

Hauffe

Pimiento

et al. 2023

Preprint

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Trait datasets are at the basis of a large share of ecology and evolutionary research, being used to infer ancestral morphologies, to quantify species extinction risks, or to evaluate the functional diversity of biological communities. These datasets, however, are often plagued by missing data, for instance due to incomplete sampling limited data and resource availabilities. Several imputation methods exist to predict missing values and have been successfully evaluated and used to fill the gaps in datasets of quantitative traits. Here we explore the performance of different imputation methods on discrete biological traits i.e. qualitative or categorical traits such as diet or habitat. We develop a bioinformatics pipeline to impute trait data combining phylogenetic, machine learning, and deep learning methods while integrating a simulation framework to evaluate their performance on synthetic datasets. Using this pipeline we run a wide range of simulations under different missing rates, mechanisms, and biases and different evolutionary models. Our results indicate that a new ensemble approach, where we combined the imputation results of a selection of imputation methods provides the most robust and accurate prediction of missing discrete traits. We apply our pipeline to an incomplete trait dataset of 1015 elasmobranch species (including sharks and rays) and found a high imputation accuracy of the predictions based on an expert-based assessment of the missing traits. Our bioinformatic pipeline, implemented in an open-source R package, facilitates the application and comparison of multiple imputation methods to make robust predictions of missing trait values in biological datasets.

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Section: Imputation Strategiesmentioning

confidence: 99%

Benchmarking imputation methods for discrete biological data

Gendre

Hauffe

Pimiento

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…In contrast to published studies, though, we show that these gender gaps remain even when controlling for electoral experience. Considering the importance of financial resources in congressional elections and evidence that women face hurdles to raising private funds (Araújo and Borges, 2013; dos Santos and Wylie, 2018; Wylie, 2020), the results of Model 2 suggest that party elites are not committed to helping women win elected office.…”

Section: Analysis Of Party Behaviormentioning

confidence: 99%

“…Nevertheless, women have achieved greater political representation in some countries than in others (Schwindt-Bayer, 2009). Brazil, for example, lags other countries in the region and the world with respect to women’s political representation (dos Santos and Wylie, 2018). Although at least 30% of the candidates that parties nominate for congressional office must be female, as of 2018, only 14.6% of seats in Brazil’s lower house of Congress are held by women.…”

Section: Introductionmentioning

confidence: 99%

Political parties and campaign resource allocation: Gender gaps in Brazilian elections

Janusz¹,

Barreiro²,

Cintron

2021

Party Politics

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Political parties shape electoral outcomes by determining who stands for election and what campaign resources they have at their disposal. The introduction of gender quotas have led party leaders to nominate more women candidates, however, those women disproportionately lose. We contend that one of the reasons that women routinely lose is because party elites withhold the campaign resources necessary to mount an effective campaign. In this paper, we test this resource gatekeeping argument using data on the provision of campaign resources in Brazil. We analyze the distribution of three different types of party resources: candidate identification numbers, financial support, and television airtime. Our findings show that party elites provide female candidates less advantageous candidate identification numbers, less financial support, and less media access than they provide male candidates. Importantly, we do not find that gender gaps in campaign contributions are attributable to differences in candidate quality. This finding suggests that even when women are recruited to run for office, party elites may still undermine their electoral prospects.

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The cost of politics: how money acts as a barrier for women in politics in the Caribbean

Johnson-Myers,

Campbell

2024

Canadian Journal of Latin American and Caribbean Studies / Revu

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The Representation of Women

Cited by 3 publications

References 1 publication

Benchmarking imputation methods for discrete biological data

Benchmarking imputation methods for discrete biological data

Political parties and campaign resource allocation: Gender gaps in Brazilian elections

The cost of politics: how money acts as a barrier for women in politics in the Caribbean

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