MétaCan
Menu
← Back to cohort
Record W6950870504 · doi:10.5683/sp3/om5ega

Environics International Environmental Monitor, 1998

2023· dataset· en· W6950870504 on OpenAlexaff

Bibliographic record

VenueBorealis · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsInnovative Research Group (Canada)
Fundersnot available
KeywordsSeriousnessVariety (cybernetics)International ActionNatural resourceAgricultureEnvironmental impact assessmentGovernment (linguistics)Resource (disambiguation)

Abstract

fetched live from OpenAlex

Environics International Environmental Monitors (EIEM) is a syndicated annual survey of global public opinion on a variety of environmental and natural resource issues. The findings of the 1998 Survey are based on the results of face-to face or telephone interviews with representative samples of about 1,000 citizens, in each of 30 countries on all continents, representing over 68 percent of the world's population. Research was conducted by respected social research institutes in each country between January 21, 1998 and May 26, 1998. A total of 47 questions were posed dealing with such topics as overall environmental concerns, possible human health impacts, seriousness of specific environmental problems, action alternatives on climate change, energy concerns and preferences, perceived benefits vs. risks of modern technology, agricultural chemicals and biotechnology, and assessments of the environmental performance of various industry sectors.

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 score0.105
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.011
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0330.040

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 head0.015
GPT teacher head0.261
Teacher spread0.245 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueBorealis→French-language works237,207→