MétaCan
Menu
Back to cohort
Record W4413062948 · doi:10.1145/3715335.3737685

(Re)working for Sustainable Futures: Climate Change and Platform Economies

2025· article· en· W4413062948 on OpenAlexaff
Ashique Ali Thuppilikkat, Hiu-Fung Chung, Kaushar Mahetaji, Anubha Singh, Nussara Tieanklin, Isabella Jaimes Rodríguez, Jen Liu, Noopur Raval, Priyank Chandra

Bibliographic record

VenueDeep Blue (University of Michigan) · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsFutures contractClimate changeSustainable developmentBusinessNatural resource economicsEconomicsPolitical scienceGeologyOceanographyFinance

Abstract

fetched live from OpenAlex

Peer Reviewed

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)0.006
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.353
Threshold uncertainty score0.923

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0030.002
Scholarly communication0.0110.006
Open science0.0020.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.3530.312

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 head0.021
GPT teacher head0.188
Teacher spread0.167 · 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 designQualitative
Domainnot available
GenreEmpirical

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueDeep Blue (University of Michigan)Same topicSharing Economy and PlatformsFrench-language works237,207