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Record W2791004936 · doi:10.1111/cag.12437

The poverty of GIS theory: Continuing the debates around the political economy of GISystems

2018· article· en· W2791004936 on OpenAlexvenueno aff
Jim Thatcher, Laura Beltz Imaoka

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographic information systemFunction (biology)Field (mathematics)PoliticsPolitical geographyPovertyDevelopment geographyGeographyEconomic geographyRegional sciencePolitical scienceHuman geographySocial scienceSociologyEconomyHistorical geographyCartographyEconomics

Abstract

fetched live from OpenAlex

Over the past several decades, GISystems and GIScience have become established and valorized within the field of geography and geographic education. With the recent explosion in daily use of devices producing spatial data, such as smartphones, has come a renewed call to broaden the purview of Critical GIS beyond the desktop and towards these new systems of capitalist accumulation. In this viewpoint, we argue that any re‐examination of the role of Critical GIS must also consider the political economy of geography and geographic education in which GISystems are used for research and taught. We explicate three registers at which GISystems function within geography: that of the individual educator, that of the GIS user, and that of the military‐industrial complex in which GISystems were and are developed.

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)0.021
metaresearch head score (Gemma)0.024
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 score0.074
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.007
Science and technology studies0.0110.130
Scholarly communication0.0210.028
Open science0.0030.009
Research integrity0.0090.013
Insufficient payload (model declined to judge)0.0070.001

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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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

Citations13
Published2018
Admission routes1
Has abstractyes

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