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Record W2523008052 · doi:10.14393/rbcv60n3-44866

LINKED AUDIO REPRESENTATION IN CYBERCARTOGRAPHY: GUIDANCE FROM ANIMATED AND INTERACTIVE CARTOGRAPHY FOR USING SOUND

2009· article· en· W2523008052 on OpenAlexafffundabout
Glenn Brauen, D. R. Fraser Taylor

Bibliographic record

VenueRevista Brasileira de Cartografia · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicRadio, Podcasts, and Digital Media
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRepresentation (politics)Computer scienceHuman–computer interactionAudio visualDimension (graph theory)Meaning (existential)PerceptionAtlas (anatomy)Set (abstract data type)MultimediaPsychology

Abstract

fetched live from OpenAlex

This paper discusses sound representation in cybercartographic atlas projects and products as one example of the application of multisensory representation in contemporary cartography. Auditory representation, like animated and interactive visual cartography, makes explicit use of the temporal dimension. Educational multimedia studies have argued that effective learning outcomes result from the coordinated interpretation of visual and auditory information and from the cognitive relations that learners develop within and between their mental representations of these materials. Based on this previous work, this paper examines the goals and motivations of research into animated and interactive cartography to determine which of those could or have been applied to the use of sound as a media for linked abstract representation in which meaning is conveyed both by the content carried by each sensory mode as well as by the manner of relations between visual and auditory representations, signified by the coordinated reactions of the visual and auditory components of atlas products to user actions. To illustrate key concepts in this discussion, the paper describes an application prototype that allows a user to examine data concerning Canada's trade with world regions using an audio-visual interface. The paper outlines a set of functional roles that this type of linked auditory representation could fulfill within an audio-visual cartography, drawing on functional analyses of interactive and animated cartography and acoustic analogies developed through the analysis of the motivations and goals of dynamic visual cartography.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.359
Teacher spread0.313 · 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 designObservational
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

Citations6
Published2009
Admission routes3
Has abstractyes

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