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Record W2791547825 · doi:10.1017/s1755773918000048

Age representation in parliaments: Can institutions pave the way for the young?

2018· article· en· W2791547825 on OpenAlexaff
Daniel Stockemer, Aksel Sundström

Bibliographic record

VenueEuropean Political Science Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCandidacyParliamentRepresentation (politics)Ethnic groupPoliticsPolitical scienceChamber of DeputiesDemographic economicsPolitical economySociologyEconomicsLaw

Abstract

fetched live from OpenAlex

Middle-aged to senior men of the ethnic majority and higher income groups are generally overrepresented in parliaments. While research on group representation has examined issues of gender, economic standing, and, more recently, ethnicity, few studies examine age groups. We argue that the design of political institutions influences the share of young adults in parliaments across nations and hypothesize that the electoral system type, age candidacy requirements, and quotas influence the share of younger deputies in national parliaments. Analyzing an original data set with a global cross-national sample, we find that proportional representation and giving candidates the right to stand in elections as early as possible (i.e. at the age of 18) matter. In contrast, quota provisions for youths are currently too selectively applied to increase the percentage of young deputies in parliament.

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)0.009
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 score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.157
GPT teacher head0.439
Teacher spread0.281 · 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

Citations138
Published2018
Admission routes1
Has abstractyes

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