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Record W6950502773 · doi:10.5683/sp3/053p1l

Family Food Expenditure Survey, 2001 [Canada]: Summary Household File

2003· dataset· en· W6950502773 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2003
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMicrodata (statistics)Consumer Expenditure SurveyConsumer expenditurePurchasingPrice indexFood away from homeConsumer price index (South Africa)

Abstract

fetched live from OpenAlex

These public-use microdata files contain information collected via the Food Expenditure Survey (FOODEX) in 2001. The Food Expenditure Survey is a companion of the Survey of Household Spending which provides detailed information on all household expenditures, but only an overall estimate for food. The 2001 Survey of Household Spending was conducted in January, February and March 2002. The primary reason for collecting food expenditure data is to monitor and periodically update the weights used in the computation of the Consumer Price Index (CPI). In addition to this, food expenditure data classified by variables such as income, household type and province, provide the basis for a variety of analytical investigations of the food purchasing habits of households in Canada. For example, the survey data are used for market analysis and nutritional studies. There are two files to this survey; the Detailed Expenditure File and the Summary Household File. The household file provides summary level food category information at a weekly level (either week one or week two or both if available) and also socio-economic characteristics of the household. The food expenditures are presented by specific food item purchased from stores, locally and on day trips. Records may be linked using the household "identification number".

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)0.001
metaresearch head score (Gemma)0.006
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.049
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.026
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0490.028

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 head0.048
GPT teacher head0.247
Teacher spread0.199 · 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
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
Published2003
Admission routes1
Has abstractyes

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