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Record W6894280184 · doi:10.5683/sp3/ixrpq9

Households and the Environment Survey, 2015 [Canada]

2015· dataset· en· W6894280184 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2015
Typedataset
Languageen
Field
Topic
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsSustainabilityContext (archaeology)Greenhouse gasEnvironmental qualityAir quality indexSurvey data collectionEnvironmental impact assessmentClimate changeQuality (philosophy)

Abstract

fetched live from OpenAlex

The Households and the Environment Survey (HES) was conducted from October 2015 to January 2016 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, 2011 and 2013. The 2015 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 2006-2013 surveys. The objective of the survey is to provide context to scientific measures of air and water quality, and greenhouse gas emissions, by gaining a better understanding of household behaviour and practices with respect to the environment. Since the HES was first conducted in 1991, environmental priorities and concerns have changed for Canadians. Changes in environmental practices and behaviours are reflective of these growing concerns. In order to gauge these changes, the HES measures some of the same environmental variables that were measured by the HES in previous cycles; however other environmental practices have been measured as well.

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)0.007
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 score0.354

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.013
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.003

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 head0.031
GPT teacher head0.245
Teacher spread0.214 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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