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Record W4392166447 · doi:10.1177/20419058241238185

Votes at 16? How the Rest of the World Does it

2024· article· en· W4392166447 on OpenAlexaboutno aff
Christine Huebner, Constanza Sanhueza Petrarca

Bibliographic record

VenuePolitical Insight · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsnot available
Fundersnot available
KeywordsRest (music)Political scienceMedicine

Abstract

fetched live from OpenAlex

In recent years, debates about reforms of the voting age – from 18 to 16 years of age – have been gearing up in many democracies around the world. Campaigns for a lowering of the voting age have emerged in more than 25 countries, with proposals in Ireland, Canada, and Australia gaining substantial traction. Most recently, Germany and Belgium pledged to enfranchise 16- and 17-year-olds for European elections and in New Zealand a bill to include young people in local elections is currently passing through the parliamentary stages. The voting age for Scottish elections was lowered in 2015, with Wales following suit five years later. But there has been little movement on demands for 16- and 17-year-olds to be allowed to vote in UK elections. Westminster has not always been so slow to change. Britain was the first country to lower the voting age from 21 to 18 in 1969, leading a wave of reforms of the voting age in democracies around the world. Debates about a further lowering of the voting age for UK elections have so far often focused on normative questions: what it means to be a voter and when young people achieve important milestones of adulthood. While debates on these questions are difficult to settle, much can be learnt about how voting age reforms affect young people’s political engagement and relationship with democracy from countries that have already lowered the minimum voting age.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0050.008
Scholarly communication0.0090.007
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0210.006

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 head0.074
GPT teacher head0.365
Teacher spread0.291 · 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 designNot applicable
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

Citations4
Published2024
Admission routes1
Has abstractyes

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