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Record W305492262 · doi:10.4018/ijmhci.2015070104

Which Way is Up?

2015· article· en· W305492262 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Mobile Human Computer Interaction · 2015
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAffordanceInteractivityFocus (optics)Locative caseComputer scienceVariety (cybernetics)Affect (linguistics)Social mediaMobilitiesSense of placeRelation (database)Human–computer interactionCognitive psychologySociologyMultimediaPsychologyCommunicationLinguisticsArtificial intelligenceWorld Wide Web

Abstract

fetched live from OpenAlex

Despite the growing prominence of locative media, its potential influence on our relationships to our places has not been well understood. Based on previous studies, this paper argues that locative media can affect our spatial relationships in various ways and thereby improve our sense of place. To understand how this can be accomplished it is important to examine the features and affordances of the medium along with user practices and outcomes in relation to place. A brief history of locative media is offered to demonstrate a progression from an early focus on wayfinding to current applications that offer a variety of place-related experiences. Subsequent sections outline four qualities about locative media that combine to differentiate it from other media in regards to place, which are its interactivity, reach, mobility, and vocality. The possible user outcomes of social navigation, autobiographical insideness, defamiliarization and refamiliarlization, and spatial interaction are examined as ways in which locative media can enhance sense of place.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.034
GPT teacher head0.313
Teacher spread0.279 · 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