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Record W4249513657 · doi:10.1002/fee.1260

Conservation culturomics

2016· review· en· W4249513657 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2016
Typereview
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsFraming (construction)Relevance (law)Environmental resource managementData scienceGeographyPolitical scienceComputer scienceArchaeology

Abstract

fetched live from OpenAlex

Culturomics is an emerging field of study that seeks to understand human culture through the quantitative analysis of changes in word frequencies in large bodies of digital texts. Culturomics research can help practitioners in nature conservation respond to cultural trends, building and reinvigorating its societal relevance. We identify five areas where culturomics can be used to advance the practice and science of conservation: (1) recognizing conservation‐oriented constituencies and demonstrating public interest in nature, (2) identifying conservation emblems, (3) providing new metrics and tools for near‐real‐time environmental monitoring and to support conservation decision making, (4) assessing the cultural impact of conservation interventions, and (5) framing conservation issues and promoting public understanding. More generally, culturomics opens up an exciting new area of research, equipping conservationists with novel tools to explore and shape human interactions with the natural world.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.280
Teacher spread0.255 · 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