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Record W2024286140 · doi:10.3138/4462-2125-1312-217t

Cartographic Signs and Arbitrariness

2004· article· en· W2024286140 on OpenAlexvenueno aff
Jan Ketil Rød

Bibliographic record

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArbitrarinessSign (mathematics)Argument (complex analysis)EpistemologyLinguisticsPhilosophyMathematics

Abstract

fetched live from OpenAlex

According to Ferdinand de Saussure's theory of the linguistic sign, the sign has two primordial characteristics, which he called the first and second principles: (1) the arbitrary nature of the sign and (2) the linear nature of the signifier. When outlining the second principle of the linear signifier, Saussure made a distinction between auditory and visual signifiers - a differentiation widely adopted by cartographers regarding cartographic signs. The first principle of the arbitrary nature of the sign has been discussed by some cartographers but is not recognized in Bertin's semiology of graphics (Bertin 1967, 1983a). Two alternative relationships constituting arbitrariness, sense versus reference, are discussed for cartographic signs. Both forms of arbitrariness are recognized as being present, and examples are given. Arbitrariness as reference is discussed, providing a theoretical argument for the use of unclassed choropleth maps in preference to classed choropleth maps.

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)0.011
metaresearch head score (Gemma)0.039
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 score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.039
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0040.032
Scholarly communication0.0100.014
Open science0.0010.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.016
GPT teacher head0.310
Teacher spread0.294 · 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

Citations5
Published2004
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