MétaCan
Menu
Back to cohort
Record W6931580763 · doi:10.5683/sp2/euyayn

Canadian Gallup Poll, February 1964, #306

2019· dataset· en· W6931580763 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2019
Typedataset
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsnot available
Fundersnot available
KeywordsRespondentUnemploymentPoliticsGovernment (linguistics)VotingPrime ministerCoalition governmentDemographicsGeneral Social Survey

Abstract

fetched live from OpenAlex

This Gallup poll aims to collect the opinions of Canadians on issues mainly of a political nature. This survey questions the respondent on their opinions about political parties and leaders, and other issues of importance to government and Canada as a whole. The respondents were also asked questions so that they could be grouped according to geographic, demographic, and social variables. Topics of interest include: which people in the world are admired most; whether Canada should recognize the communist government in China; defence policy; Diefenbaker's performance as the leader of the opposition; whether Easter should be held on a fixed date; federal elections; inflation predictions; labour leaders' wisdom; whether the Liberal party should unite with the NDP; Pearson's performance as Prime Minister; preferred political parties; sex education in highschool; unemployment predictions; union membership; the vote of confidence in Diefenbaker by the Conservative party; 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: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.042
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.015
Science and technology studies0.0040.001
Scholarly communication0.0040.001
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0420.047

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 head0.008
GPT teacher head0.225
Teacher spread0.216 · 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
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

Explore more

Same venueBorealisSame topicAdvanced machining processes and optimizationFrench-language works237,207