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Record W2049828530 · doi:10.1111/1541-0064.00025

Gendering environmental geography

2003· article· en· W2049828530 on OpenAlexaffvenueabout
Maureen G. Reed, Bruce Mitchell

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsUniversity of WaterlooUniversity of Saskatchewan
Fundersnot available
KeywordsEnvironmental studiesSociologyEnvironmental justicePoliticsHuman geographyCitizen journalismFeminismEnvironmental ethicsCritical geographySocial sciencePolitical scienceCultural geographyGender studiesLaw

Abstract

fetched live from OpenAlex

Despite sharing common interests in being advocates for social change, feminist and environmental geographers have yet to acknowledge interests they share in common. Environmental geographers, particularly those focused on policy and institutional analysis, have not embraced feminist theories or methodologies, while few feminist geographers have engaged issues associated with environmental policy‐making. Our purpose is to initiate a dialogue about how linkages might be forged between feminist and environmental geography, particularly among Canadian environmental geographers working on institutional and policy analysis. We begin by illustrating that environmental geographers working on Canadian problems have neglected to introduce gender as an analytical category or feminist conceptual frameworks to guide their research. Second, we identify four feminist research approaches that should also be pursued in environmental geography. Third, we consider examples of how feminist perspectives might be incorporated in three themes of environmental geography: institutional and policy analysis, participatory environmental and management systems and alternative knowledge systems. Fourth, we consider two research frameworks—political ecology and environmental justice—and suggest that these may be useful starting points for integrating feminist analysis into environmental geography. Last, we summarise our suggestions for how future research of feminist and environmental geographers could benefit from a closer association.

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 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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.216
Teacher spread0.205 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations28
Published2003
Admission routes3
Has abstractyes

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