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Record W2920982266 · doi:10.70064/mt.v2i1.691

Bergson's GIS: Experience, Time and Memory in Geographical Information Systems

2018· article· en· W2920982266 on OpenAlexaff
Rob Shields

Bibliographic record

VenueMedia theory. · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTemporalityPerceptionEmbodied cognitionMovement (music)Space (punctuation)Duration (music)Computer scienceMetric (unit)Time perceptionSpacetimeDynamics (music)Basis (linear algebra)Cognitive scienceCognitive psychologyHuman–computer interactionSociologyAestheticsPsychologyEpistemologyArtificial intelligenceArtMathematicsEngineering

Abstract

fetched live from OpenAlex

Geographical Information Systems (GIS) intended as digital forms of mapping struggle to represent time, change and temporality. The assumption of a static Cartesian, metric space of two or three dimensions only and defined by coordinates makes it difficult to create GIS and Historical GIS (HGIS) interfaces and representations that include the dynamics Bergson and later Deleuze describe. They argue that temporal memory is the basis of attention in encounters and perception of situations. This “affiliation” of the past enlivens the present perceptual life of experience. Video gaming and the combination of Google Earth and Street View are explored as limited alternatives that draw on embodied, kinaesthetic experiences of movement in space to open up or “uncurl” extra dimensions that allow more nuance in digital representations of spatiotemporal encounters, and the many modes and rhythms of duration found in the environment.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.277
Teacher spread0.267 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2018
Admission routes1
Has abstractyes

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