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Record W2014969374 · doi:10.1353/cpp.2010.0001

The Importance of the Long Form Census to Canada

2010· article· en· W2014969374 on OpenAlexaffvenueabout
David A. Green, Kevin Milligan

Bibliographic record

VenueCanadian Public Policy · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCensusDeci-American Community SurveyGovernment (linguistics)GeographyPublic administrationEconomic growthPolitical scienceDemographyEconomicsSociologyPopulationLaw

Abstract

fetched live from OpenAlex

In June the federal government published plans to replace the mandatory long form census with a new National Household Survey (NHS) for the 2011 Census cycle. The new NHS is to be circulated to more households but will be voluntary rather than manda tory. The announcement generated a response unique both for its breadth across civil society and its near uniformity. The breadth reflects the plethora of uses for census data, stretching into so many important deci sions made by businesses, municipal and provincial governments, and non-profits. The near uniformity

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)0.009
metaresearch head score (Gemma)0.058
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: Empirical · Consensus signal: none
Teacher disagreement score0.164
Threshold uncertainty score0.970

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.016
Science and technology studies0.0090.004
Scholarly communication0.0100.004
Open science0.0030.004
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0150.002

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 head0.261
Teacher spread0.248 · 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
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

Citations32
Published2010
Admission routes3
Has abstractyes

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