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Record W2146323367 · doi:10.1177/1354068810386838

How many political parties are there, really? A new measure of the ideologically cognizable number of parties/party groupings

2011· article· en· W2146323367 on OpenAlexaboutno aff
Bernard Grofman, Reuben Kline

Bibliographic record

VenueParty Politics · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsnot available
Fundersnot available
KeywordsParty platformIdeologyPluralism (philosophy)PoliticsLawPolitical sciencePolitical systemParliamentSociologyLaw and economicsEpistemologyPhilosophyDemocracy

Abstract

fetched live from OpenAlex

We offer a new measure of the ideologically cognizable number of political parties/party groupings that is intended to be complementary to the standard approach to counting the effective number of political parties – the Laakso–Taagepera index (1979). This approach allows the possibility of precise measurement of concepts such as polarized pluralism or fragmented bipolarism and is applicable to both unidimensional and multidimensional representations of party locations. Using recent CSES (Comparative Study of Electoral Systems) data on one-dimensional representations of party locations in four real-world examples (two of which are available in an online appendix), we find that Slovenia, treated initially as a five-party system, has its optimal reduction as a two-bloc/party system, as does Spain, which is treated initially as a four-party system. However, Canada, treated initially as a four-party system, has its optimal reduction as a three-bloc/party system if we look at a unidimensional representation of the party space, while it remains a four-bloc system if we draw on Johnston’s two-dimensional characterization of Canadian political competition. Finally, the Czech Republic, initially a five-party system, is optimally reduced to a system with four party groupings.

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)0.001
metaresearch head score (Gemma)0.001
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.111
GPT teacher head0.322
Teacher spread0.210 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations13
Published2011
Admission routes1
Has abstractyes

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