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Record W2115207053 · doi:10.24124/c677/2012253

"Getting Better All the Time?": Leadership Selection and the Manitoba NDP

2013· article· en· W2115207053 on OpenAlexaffvenueabout
Jared J. Wesley, Brett Allen Loewen

Bibliographic record

VenueCanadian Political Science Review · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsUniversity of ManitobaUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsDelegateSelection (genetic algorithm)ConventionPolitical scienceDemocracyPublic administrationPublic relationsLaw and economicsSociologyLawComputer sciencePolitics

Abstract

fetched live from OpenAlex

In failing to achieve many of the benefits associated with delegate conventions, and realizing most of their shortcomings, the Manitoba New Democratic Party appears poised to adopt a new method of leadership selection. Based on the party’s base of support, history, and experiences during the most recent leadership race in 2009, the following analysis suggests NDP members may look most favourably upon a “hybrid” approach to selecting their next leader. This would allow the party to maintain many of the advantages of the convention model, while incorporating the strengths of a one-member, one-vote system.

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)0.004
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.091
GPT teacher head0.338
Teacher spread0.247 · 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
GenreCommentary

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

Citations2
Published2013
Admission routes3
Has abstractyes

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