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Record W2607452614 · doi:10.5539/jpl.v10n3p13

Constitution-Building Bodies and the Sequencing of Public Participation A Comparison of Seven Empirical Cases

2017· article· en· W2607452614 on OpenAlexvenueno aff
Abrak Saati

Bibliographic record

VenueJournal of Politics and Law · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsnot available
FundersVetenskapsrådet
KeywordsConstitutionCompromisePoliticsAuthoritarianismDemocracyNegotiationPolitical scienceLawLaw and economicsPromulgationPublic administrationSociology

Abstract

fetched live from OpenAlex

Constitution-building is one of the most salient aspects of transitional processes, from war to peace or from authoritarian rule, in terms of establishing and strengthening democracy. This paper is part of a research project that aims to identify the circumstances under which constitution-building can strengthen democracy after violent conflict and during transitions from authoritarian rule. Previous research has indicated that the actions and relations of political elites from opposing political parties when making the constitution has bearing on the state of democracy post promulgation, but that the careful sequencing of public participation in the process can be of relevance as well. This paper conducts a systematic analysis of seven empirical cases and focuses the investigation to the type of constitution-building body that has been employed and to during what stage of the process the general public have been invited to participate. It concludes that popularly elected constitution-building bodies tend to include a broad range of political parties and that they, additionally, tend to have rules of procedure that encourage compromise and negotiation, whereas appointed bodies are dominated by one single party or one single person and do not have rules of procedure that necessitate compromise. The paper also discusses the potential need for political elites to have negotiated a number of baseline constitutional principles prior to inviting the general public to get involved in the constitution-building process, and concludes that this is an area of research in need of further in-depth empirical case-studies.

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)0.021
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.079
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.007
Science and technology studies0.0080.014
Scholarly communication0.0050.004
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.187
GPT teacher head0.433
Teacher spread0.246 · 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 designQualitative
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

Citations7
Published2017
Admission routes1
Has abstractyes

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