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Record W2135658979 · doi:10.3138/carto.44.4.240

Performative Atlases: Memory, Materiality, and (Co-)Authorship

2009· article· en· W2135658979 on OpenAlexvenueno aff
Veronica della Dora

Bibliographic record

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPerformative utteranceMateriality (auditing)ConceptualizationMnemonicReading (process)AestheticsSociologyVisual artsArtHistoryPsychologyLinguisticsCognitive psychologyPhilosophy

Abstract

fetched live from OpenAlex

Maps have traditionally been conceptualized as visual representations and studied for what they represent. In the past few years, however, scholars from different disciplines have started to approach them from new perspectives. Broadly speaking, art historians have shown increased interest in their materialities, and geographers and map historians in their social and performative aspects. This article reviews and synthesizes these approaches using the example of the atlas in its earliest and latest incarnations (Abraham Ortelius’ Theatrum Orbis Terrarum and Google Earth). Atlases are conceptualized as mnemonic tools activated through different types of personal encounters that are at once visual and tactile. Focusing on performative encounters between atlases and their users, the article calls for a re-conceptualization of maps as fluid objects that are always in the making. It also invites a reading of the history of cartography as a history of interactions and co-authorships between map-makers and map users.

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)0.006
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.007
Science and technology studies0.0050.018
Scholarly communication0.0140.021
Open science0.0010.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.023
GPT teacher head0.352
Teacher spread0.329 · 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.

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

Citations46
Published2009
Admission routes1
Has abstractyes

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Same venueCartographica The International Journal for Geographic Information and GeovisualizationSame topicGeographic Information Systems StudiesFrench-language works237,207