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Record W2008921082 · doi:10.1016/j.envsci.2014.08.003

Resilience scientists as change-makers—Growing the middle ground between science and advocacy?

2014· article· en· W2008921082 on OpenAlexaff
Manjana Milkoreit, Michele‐Lee Moore, Michael Schoon, Chanda L. Meek

Bibliographic record

VenueEnvironmental Science & Policy · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEcosystem dynamics and resilience
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsResilience (materials science)Corporate governancePsychological resilienceScience policyPoliticsValue (mathematics)SociologyEnvironmental ethicsPolitical scienceSet (abstract data type)Citizen journalismEngineering ethicsEnvironmental resource managementPublic relationsPublic administrationComputer scienceLawBusinessSocial psychologyPsychology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.141
metaresearch head score (Gemma)0.182
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.979
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1410.182
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0070.004
Science and technology studies0.0210.092
Scholarly communication0.0590.120
Open science0.0060.043
Research integrity0.0430.055
Insufficient payload (model declined to judge)0.0300.004

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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
GenreCommentary

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

Citations60
Published2014
Admission routes1
Has abstractno

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