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Record W3215040550 · doi:10.1017/asjcl.2021.36

Constituting and Regulating Democracy: Kenya's Electoral Commission and the Courts in the 2010s

2021· article· en· W3215040550 on OpenAlexaff
Richard Stacey, Victoria Miyandazi

Bibliographic record

VenueAsian Journal of Comparative Law · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDeferenceSupreme courtPolitical scienceLawDemocracyRemand (court procedure)CommissionJudicial deferencePolitics

Abstract

fetched live from OpenAlex

Abstract In August 2017, responding to a petition from the losing candidate in the presidential election held days before, the Supreme Court of Kenya declared the results of the election null and void. Dramatic in itself, the decision stands in surprising contrast to the same Court's decision to uphold the 2013 election results following a similar petition. Beyond the different outcomes in 2013 and 2017, the Court's jurisprudential approach to the two petitions was markedly different. The Court showed significant deference to the Independent Elections and Boundaries Commission (IEBC) in 2013, and did not seriously interrogate its conclusion that the election had been free and fair. In 2017, however, the Court scrutinised the IEBC's process and paid close attention to the reasons it gave for declaring the result free and fair. This article considers the difference in the Court's approach in two ways. First, from a prescriptive perspective, it suggests when it is appropriate for courts to closely scrutinise the work of elections management boards and other ‘fourth branch’ institutions protecting democracy (IPDs). The article argues that where an IPD performs a function that is constitutive of rights, courts should be prepared to intervene. By contrast, where an IPD performs a function that is regulative of already constituted rights, courts of review should act with deference. On this basis, the article concludes that the Court should have engaged in a deeper review of the IEBC's 2013 decision. Second, from a descriptive perspective, the article suggests that the difference between the Court's 2013 and 2017 approaches can be explained by waning levels of public trust in the IEBC alongside growing levels of public confidence in the judiciary.

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)0.009
metaresearch head score (Gemma)0.015
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: none
Teacher disagreement score0.304
Threshold uncertainty score0.604

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.015
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0290.014
Scholarly communication0.0150.005
Open science0.0010.004
Research integrity0.0130.009
Insufficient payload (model declined to judge)0.0060.000

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 head0.038
GPT teacher head0.332
Teacher spread0.294 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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