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Record W4378843736 · doi:10.1177/02780771231162196

Integrating Historical Ecology and Environmental Justice

2023· article· en· W4378843736 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

VenueJournal of Ethnobiology · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsScholarshipFraming (construction)Environmental justiceEnvironmental ethicsRealmEthnobiologySociologyEnvironmental studiesCultural heritageEcologyContext (archaeology)AnthropologyPolitical scienceArchaeologyGeographyLawBiology

Abstract

fetched live from OpenAlex

Environmental justice studies (EJS) provides a framework for interdisciplinary research and advocacy in the realm of cultural heritage research and management. Ethnobiologists, in particular those who focus on environmental archaeology, are no strangers to the heritage arena as our scholarship commonly concerns “cultural keystone places,” which are rich with meaning for one or more groups of people. Three dimensions and three core concepts of EJS can serve as guideposts to research centering on these significant places. These EJS concepts align and intersect with core principles of historical ecology (HE), particularly through the study of landscapes as complex systems. This paper highlights how environmental justice and HE can be conceptually integrated. This EJS-HE framework is relevant to research design in environmental archaeology and more broadly ethnobiology, a framing to be adopted at the beginning of the research process that explicitly considers whether a research question is ethical to approach within a particular heritage context.

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)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.113
GPT teacher head0.256
Teacher spread0.143 · 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