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Record W6950684563 · doi:10.5683/sp2/juetq5

Canadian Gallup Poll, May 1962, #295

2019· dataset· en· W6950684563 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2019
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
Fundersnot available
KeywordsVotingPoliticsPrime ministerDemographicsPrime (order theory)Voting behavior

Abstract

fetched live from OpenAlex

The purpose of this Gallup poll is to get the political views and opinions of Canadians before an election. Nearly all of the questions deal either directly with the election, voting, or the preferred parties and politicians of the respondent. The respondents were also asked questions so that they could be grouped according to geographic, demographic, and social variables. The topics of interest include: car ownership; Diefenbaker as Prime Minister; electoral ridings; the upcoming federal election; opinions towards what the greatest problem currently facing Canada is; whether respondents' names are on the electoral list; Pearson as the next Prime Minister; whether political debates should be on television; preferred political parties; union membership; and voting behaviour. Basic demographics variables are also included.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.064
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.019
Science and technology studies0.0040.001
Scholarly communication0.0050.001
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0640.056

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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2019
Admission routes1
Has abstractyes

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