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Record W4388146778 · doi:10.24124/c677/20201796

The 2018 Provincial Election in New Brunswick

2021· article· en· W4388146778 on OpenAlexaffvenueabout
Jamie Gillies, JP Lewis, Tom Bateman

Bibliographic record

VenueCanadian Political Science Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsGovernment of New BrunswickUniversity of New Brunswick
Fundersnot available
KeywordsAllianceMainstreamCaucusPolitical scienceLegislaturePoliticsPolitical economyGovernment (linguistics)Public administrationCriticismGeneral electionLawSociology

Abstract

fetched live from OpenAlex

New Brunswick’s 2018 election produced a minority legislature, the first in a century. The major parties continue to decline in voter support, and two new parties now have a presence in the Assembly. The election brings New Brunswick’s electoral politics increasingly into the modern Canadian mainstream; one new caucus is the Greens. In other respects, the election made the old new again. The populist People’s Alliance gained three seats partly on the basis of criticism of bilingualism policy. The Alliance and the Progressive Conservatives, in an informal alliance to govern, are all but confined to the anglophone parts of the province, while the defeated Liberals have all their strength in the Acadian north-east. The campaign mattered, as did constitutional conventions. The Liberals squandered a large lead in the polls, and the parties struggled to sort out the conventions of government formation.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.081
Threshold uncertainty score0.587

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0060.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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 designObservational
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

Citations0
Published2021
Admission routes3
Has abstractyes

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