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Record W3091713470 · doi:10.3138/cart.53.3.intro

Decolonizing the Map: Recentering Indigenous Mappings

2020· article· en· W3091713470 on OpenAlexaffvenue
Reuben Rose‐Redwood, Natchee Blu Barnd, Annita Lucchesi, Sharon Dias, Wil Patrick

Bibliographic record

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2020
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsIndigenousPraxisColonialismEmpirePoliticsAnthropologyGeographySociologyPolitical scienceArchaeologyEcologyLaw

Abstract

fetched live from OpenAlex

For over five centuries, cartographic map-making has played a pivotal role as a political technology of empire-building, settler colonialism, and the dispossession of Indigenous lands. Yet Indigenous peoples themselves have long engaged in their own mapping practices to share ancestral knowledge, challenge colonial rule, and reclaim Indigenous “place-worlds.” Although there is now a sizable body of scholarly literature on the mapping of empire, this special issue on “Decolonizing the Map” aims to recenter Indigenous mappings and decolonial cartographies as spatial practices of world-making. In this introductory article, we provide an overview of the theory and praxis of decolonial mapping and outline the key themes of the contributions to the present special issue. Drawing upon insights from this edited collection, we conclude that decolonial mapping requires a recentering of Indigenous geographical knowledge, respect for Indigenous protocols, and the active participation of Indigenous peoples in the mapping process itself if the project of decolonizing the map is to truly move beyond the colonial cartographic frame.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.357
Teacher spread0.321 · 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 designNot applicable
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

Citations109
Published2020
Admission routes2
Has abstractyes

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