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Record W1486534458 · doi:10.1111/cag.12093

Feminist geographies of new spatial media

2014· article· en· W1486534458 on OpenAlexfundvenueno aff
Agnieszka Leszczynski, Sarah Elwood

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaWisconsin Alumni Research FoundationNational Science Foundation
KeywordsAffordanceSociologyPoliticsSocial mediaDigital mediaContext (archaeology)Spatial contextual awarenessPolitical scienceGeographyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Critical GIS emphasized the ways in which social, political, and economic inequalities are (re)produced through spatial information technologies and attendant practices. In the mid‐1990s through the early 2000s, feminist interventions challenged the presumed gender neutrality and universality of GIS and brought gender to the fore of Critical GIS concerns. However, the rise of nascent web‐based spatial information technologies—or new spatial media—signals the need to extend this work to determine how it is that gender matters differently in this newly diversified, pervasive, and public context of geographic information technologies. Building on an analysis of online commentaries and an assessment of the functions and promotional material of several illustrative applications, we argue that gender continues to “matter” vis‐à‐vis new spatial media in three key dimensions: i) new practices of data creation and curation; ii) affordances of new technologies; and iii) new digital spatial mediations of everyday life.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0080.034
Scholarly communication0.0090.008
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.012
GPT teacher head0.219
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations128
Published2014
Admission routes2
Has abstractyes

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Same venueCanadian Geographies / Géographies canadiennesSame topicGeographic Information Systems StudiesFrench-language works237,207