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Record W7096892018

Proceedings of the Survey Methods Section ENVIRONMENTAL SURVEYS AND INDICATORS- CONCEPTUAL AND METHODOLOGICAL CHALLENGES

2015· article· en· W7096892018 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsSection (typography)Agency (philosophy)Data collectionEnvironmental dataSurvey methodologyEnvironmental research
DOInot available

Abstract

fetched live from OpenAlex

Statistics Canada has recently embarked on an expansion of its environmental statistics program that will see more than a doubling of the number of surveys and an increase in the output of derived statistical products such as indicators and accounts. For the first time, the agency will begin regular collection of environmental information directly from households. It is also proposing a significant foray into the collection of pollution emissions data from businesses. New indicators of environmental

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)0.390
metaresearch head score (Gemma)0.443
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.390
Threshold uncertainty score0.753

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3900.443
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0070.015
Science and technology studies0.0060.016
Scholarly communication0.0210.009
Open science0.0050.006
Research integrity0.0090.016
Insufficient payload (model declined to judge)0.0270.013

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 head0.244
GPT teacher head0.398
Teacher spread0.154 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreMethods

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 routes1
Has abstractyes

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