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Record W4312943765 · doi:10.1017/s003224742100070x

Mapping Antarctic and Arctic Women: An exploration of polar women’s experiences and contributions through place names

2022· article· en· W4312943765 on OpenAlexaff
Carol Devine

Bibliographic record

VenuePolar Record · 2022
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsCentre for Global Health ResearchYork University
Fundersnot available
KeywordsIndigenousGlobeExpansiveColonialismGeographyArcticThe arcticHistorySense of placeToponymyGender studiesGenealogyEthnologySociologyArchaeologyOceanographyPsychologyGeologyEcology

Abstract

fetched live from OpenAlex

Abstract In this commentary, I investigate the Poles differently, and in situ, rather than only as stereotypically barren uninhabited expansive places on a globe or maps. The human stories are behind the relatively white space on which few place names are marked. But the more visible ones are made and told through a male-dominated, colonial narrator and mapmaker, until more recently. Cartography, like history, has overwhelmingly documented men’s worlds, stories, dominations and accomplishments, creating a virtual whiteout of women’s and notably Indigenous women’s stories also in polar regions. In this commentary, I report on a journey into (re)mapmaking I did of women’s stories told through female place names and toponymies of women especially in the Antarctic, through a crowd-sourced project, Mapping Antarctic Women. I explore not only mapping female place names and women’s stories in the Arctic, exploring gendered, colonial and western culture mapping but also newer digital Indigenous place name mapping and also mapping of human-exacerbated changes in the ice that makes the Antarctic map.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
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
Bibliometrics0.0000.000
Science and technology studies0.0050.000
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 head0.048
GPT teacher head0.352
Teacher spread0.304 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations6
Published2022
Admission routes1
Has abstractyes

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