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Record W2096384768 · doi:10.1111/lsq.12056

Enfranchisement, <scp>M</scp>alapportionment, and <scp>I</scp>nstitutional <scp>C</scp>hange in <scp>G</scp>reat <scp>B</scp>ritain, 1832–1868

2014· article· en· W2096384768 on OpenAlexafffund
Christopher Kam

Bibliographic record

VenueLegislative Studies Quarterly · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBallotFranchisePolitical scienceOpposition (politics)AdvertisingVotingLawPolitical economyLaw and economicsBusinessEconomicsPoliticsMarketing

Abstract

fetched live from OpenAlex

This article examines why after 35 years of repeatedly rejecting the secret ballot, the British House of Commons enacted it with the Ballot Act of 1872. Drawing on roll‐call votes, I show that parliamentary opposition to the secret ballot was invariant between 1832 and 1867. In 1867, however, the Second Reform Act significantly extended the electoral franchise and substantially redistributed parliamentary seats; the House elected immediately following these changes to pass the Ballot Act of 1872. I show that a key reason for the change in the House's attitude on the ballot was that anti‐ballot MPs whom the redistribution threatened to expose to electoral competition were disproportionately likely to retire prior to the 1868 election. These results imply that it was the anticompetitive effects inherent in the gross malapportionment of the older electoral system rather than the restricted nature of the franchise that insulated MPs from public pressure and kept parliamentary opinion on the secret ballot in stasis. This is a useful lesson because while almost all modern democracies operate on a universal adult suffrage, many continue to be marked by significant malapportionment.

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 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)0.003
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.600
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0040.009
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.029
GPT teacher head0.304
Teacher spread0.275 · 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; both teacher heads agree on what is shown here.

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
Published2014
Admission routes2
Has abstractyes

Explore more

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