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Record W2338607835 · doi:10.14288/1.0094410

The validity of citizen attitudes as conveyed to politicians and planners through participation and representation

2010· article· en· W2338607835 on OpenAlexaboutno aff
Kenneth James McKeen

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
Fundersnot available
KeywordsRepresentation (politics)Political sciencePublic relationsSocial psychologyPsychologyPoliticsLaw

Abstract

fetched live from OpenAlex

Information conveyed to city planners and politicians for use in decision making may not reflect the full range of opinions found in an urban population. People who convey the feelings of the Vancouver population - the participators - hold significantly different ideas about the relative importance of various urban issues than non- participators. People from different local areas of Vancouver also hold differing ideas about the importance of some urban issues. A reliable ten-variable scale of participation developed as part of the study was used to measure the level of participation for each of 779 Vancouver respondents and to determine the means of participation for each of twenty-two Vancouver Local Areas and Point Grey-U.B.C. in which the respondents lived. The comparative usefulness of participation and local neighbourhood areas as predictors of the perceived importance of thirty-five urban issues was tested. Both predictors are statistically significant, but with low prediction coefficients. The differences among local areas in level of participation and in "within area" range of participation have implications for civic administration and planning in Vancouver. A ward system of city government may facilitate an election of members to council which is more spatially representative yet equally efficient than the present at-large system. The existing local area planning system appears to be generally well suited for responding to differences among the local areas in both level and range of participation.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.339
Teacher spread0.293 · 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 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
Published2010
Admission routes1
Has abstractyes

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