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Record W2134334413 · doi:10.24124/c677/2012177

Public Opinion Research Procurement in the Saskatchewan Government: Polling for the Public Good?

2013· article· en· W2134334413 on OpenAlexaffvenueabout
Andrea Rounce

Bibliographic record

VenueCanadian Political Science Review · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSociopolitical Dynamics in Nepal
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPublic opinionPollingGovernment (linguistics)PoliticsPublic relationsRelevance (law)Public administrationPolitical scienceProcurementDemocracyBusinessLawMarketing

Abstract

fetched live from OpenAlex

Public opinion research has become a key element of both governmental policy-making and communications strategies in most democratic jurisdictions. However, there are differences among jurisdictions in how public opinion research is procured, how the results of this research are disseminated, and what contribution this research might make to the “public good”. Saskatchewan’s approach to the commissioning and publication of public opinion research raises questions about how government approaches procurement of polling and other public opinion research, how this research supports government decision-making (including agenda-setting) and communications strategies, whether or not it should have the role it does in decision-making, and what – if any – contribution polling makes to the overall good of the citizens in the province. Given the requirement of public release, how do political actors see the relevance and importance of public opinion research in policy-making?

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)0.045
metaresearch head score (Gemma)0.046
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 score0.917
Threshold uncertainty score0.600

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.046
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.012
Science and technology studies0.0100.010
Scholarly communication0.0180.006
Open science0.0030.007
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.222
GPT teacher head0.436
Teacher spread0.214 · 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

Citations1
Published2013
Admission routes3
Has abstractyes

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