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Record W652344409

CENSUS PLACE OF WORK/MODAL CHOICE VARIABLES

2001· article· en· W652344409 on OpenAlexaboutno aff
D Kriger, Moira Fathy Baker, D Palsat, Charles McMillan, Daniel R. MESHER

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCensusRespondentJourney to workWork (physics)ResidenceVariable (mathematics)American Community SurveyGeographyModalRegional scienceEconomicsPublic transportTransport engineeringPolitical scienceSociologyEngineeringPopulationDemographic economicsDemography
DOInot available

Abstract

fetched live from OpenAlex

The publication summarizes best practices for the use of the place of work and modal choice variables collected in the Census of Canada and draws from related experience in this country, the United States and Australia. The place of work variable provides a means of relating the locations of the census respondent's place of residence and place of work, and how these change over time. The modal choice variable records the usual means of travel to work. The synthesis of practice describes the two variables and their relationship to the census. The structure of the census questions is described and compared with similar questions from the American and Australian censuses. Transportation planners, urban planners, policy makers, developers and financial analysts in both the public and private sectors are expected to use the new publication when they consider the location and timing of new transportation infrastructure, land development, investment in new businesses and social and fiscal policies, among other issues. (A)

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)0.008
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: Other · Consensus signal: none
Teacher disagreement score0.096
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.014
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0200.006

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 head0.310
Teacher spread0.264 · 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
GenreOther

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
Published2001
Admission routes1
Has abstractyes

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