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Record W6913156592 · doi:10.5683/sp3/fp1oay

Postal Code Federal Riding File [Canada], December 2003, Census of Canada 2001

2025· dataset· en· W6913156592 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsParliamentPostal serviceCode (set theory)CensusZip codeRepresentation (politics)Product (mathematics)

Abstract

fetched live from OpenAlex

<p>The Postal Codes by Federal Ridings File (PCFRF) is a digital file which provides a link between the six- character postal code and Canada’s federal electoral districts (which are also known as federal ridings).</p> <p>Elections Canada defines a federal electoral district (FED) as any place or territorial area entitled to return a Member of Parliament (MP) to serve in the House of Commons. Federal electoral district legal limits and descriptions are the responsibility of the Chief Electoral Officer, and are usually revised every ten years after the results of the decennial census. There are 308 FEDs in the 2003 Representation Order, the most recent revision of the federal electoral districts limits.</p> <p>Some postal codes straddle one or more FED boundaries. Users often link the postal code in their data set to the FED in the PCFRF. When performing this link, users should be aware that the postal code in their data set may represent a mailing address used by a person, not necessarily where the person actually resides. Similarly, a postal code in a business-based mailing address may not necessarily indicate where the business activity took place.</p> <p>The reference date for postal codes contained in the PCFRF is the same date as the postal codes contained in the Postal Code Conversion File (PCCF) product released concurrently with this version of the PCFRF</p>

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.041
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.249
Teacher spread0.235 · 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.

Study designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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