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Record W4390674622 · doi:10.1080/02681102.2023.2298876

Visual imagery and the informal city: examining 360-degree imaging technologies for informal settlement representation

2024· article· en· W4390674622 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

VenueInformation Technology for Development · 2024
Typearticle
Languageen
FieldComputer Science
TopicVideo Surveillance and Tracking Methods
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsInformal settlementsSettlement (finance)PerceptionRepresentation (politics)Human settlementSociologyPhotographyGeographyComputer scienceVisual artsPsychologyArchaeologyPolitical scienceArt

Abstract

fetched live from OpenAlex

Informal settlements are a feature of many cities worldwide, yet information about their social and spatial conditions is often limited to what can be obtained from external observation. Remote sensing and landscape photography are used to acquire information about informal settlements, but images taken from the air or at a distance obscure their complexity, advancing a reductionist imaginary of informality in the minds of outsiders. As part of a project in an informal settlement in Johannesburg, this paper explores the potential of 360-degree imagery as a realist form of spatial representation, towards highlighting the diverse spatial forms, contexts, and lived realities of the informal city. Findings demonstrate the benefits of 360-degree imagery in comparison to other spatial and visual representation methods. Findings also reveal the need for more research into the impacts of this technology on viewer perspectives and perceptions, both visual-cognitive and in terms of intersubjectivity and power relations.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.943
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.001
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 head0.040
GPT teacher head0.322
Teacher spread0.283 · 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