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Record W4413403543 · doi:10.1177/20438206251371225

Place-based approaches to develop the foundations and diversities of energy geographies

2025· article· en· W4413403543 on OpenAlex
Christina E. Hoicka

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDialogues in Human Geography · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsUniversity of Victoria
FundersCanada Research Chairs
KeywordsEconomic geographySociologyEnergy (signal processing)GeographyRegional science

Abstract

fetched live from OpenAlex

Although geographers are well-positioned to increase the impact and salience of critical, spatially centred and place-based scholarship about energy, highlight that energy geographies do not occupy a central position in climate scholarship, or within human geography, and suggest three pathways to bring energy geographies to the centre of the discipline. Taking a biophysically informed, experientially grounded, place-based perspective to expand on the positioning of energy geographies and justice, I argue that although energy geography may occupy a marginal position within both human geography and energy scholarship, its concerns often lie at the heart of understanding the drivers and dynamics of energy transitions. The practice of actively listening to students and clearly articulating our ideas to help them situate themselves within the subfield are crucial while also enabling energy geographers to refine and expand the conceptual and theoretical foundations of energy geographies. This pedagogical engagement fosters a more heterogeneous and inclusive scholarly community.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
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 head0.056
GPT teacher head0.272
Teacher spread0.216 · 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