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Record W4399081679 · doi:10.1029/2024av001298

AGU Publications Updates Authorship Policy to Foster Greater Equity and Transparency in Global Research Collaborations

2024· article· en· W4399081679 on OpenAlexaff
Marguerite A. Xenopoulos, Ben Bond‐Lamberty, Ankur R. Desai, D. N. Huntzinger, Paula Buchanan, Amy E. East, Arvind Singh, Paige Wooden, Kevin Jewett, Mia Ricci

Bibliographic record

VenueAGU Advances · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsTrent University
FundersUniversity of GhanaBattelle
KeywordsTransparency (behavior)Equity (law)Political scienceScience policyPublic relationsWork (physics)Research policyPublic administrationEngineering

Abstract

fetched live from OpenAlex

Abstract AGU Publications encourages research collaborations between regions, countries, and communities. When well‐resourced researchers complete research or field work in low‐resourced settings while excluding local communities or researchers from the process, this can be referred to as parachute science or helicopter research. To help address concerns of parachute science and to promote greater equity and transparency in global research collaborations, AGU Publications has updated its authorship policy across its scholarly journals. The implementation of this policy follows a successful 18‐month pilot at JGR: Biogeosciences . For research completed in low‐resourced regions, authors are encouraged to include a disclosure statement pertaining to the ethical and scientific considerations of their research collaborations.

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)0.321
metaresearch head score (Gemma)0.517
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.838

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3210.517
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0090.009
Science and technology studies0.0120.010
Scholarly communication0.0380.025
Open science0.0090.016
Research integrity0.0510.023
Insufficient payload (model declined to judge)0.0460.053

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 head0.111
GPT teacher head0.447
Teacher spread0.336 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
GenreEditorial

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

Citations6
Published2024
Admission routes1
Has abstractyes

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