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Record W6950684478 · doi:10.5683/sp3/m2u8nz

Households and the Environment Survey, 2013 [Canada]

2015· dataset· en· W6950684478 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2015
Typedataset
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsSustainabilityGreenhouse gasSurvey data collectionEnvironmental qualityQuality (philosophy)Work (physics)Air quality indexEnvironmental data

Abstract

fetched live from OpenAlex

This dataset refers to Version 2 of the Households and Environment Survey (HES), 2013. The HES was conducted in October and November 2013 as a supplement to the Canadian Community Health Survey. The survey was designed to specifically address the needs of its funding source the Canadian Environmental Sustainability Indicators (CESI) project, a joint venture between Statistics Canada, Environment Canada and Health Canada. The CESI project reports annually on air quality, water quality and greenhouse gas (GHG) emissions in Canada using indicators to identify areas of importance to Canadians and monitor progress. The HES was first conducted in 1991, 1994 and more recently in 2006, 2007, 2009 and 2011. The 2013 survey offers an expanded view on household behaviours that relate to the environment but allows for comparisons with the 1994 survey for some indicators and most of the indicators from the 2006, 2007 and 2009 surveys.

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)0.009
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 score0.032
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.023
Science and technology studies0.0020.000
Scholarly communication0.0030.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.016

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 head0.269
Teacher spread0.254 · 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
Published2015
Admission routes2
Has abstractyes

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