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Record W2010661108 · doi:10.1002/asi.21618

Visual approaches and photography for the study of immediate information space

2011· article· en· W2010661108 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

VenueJournal of the American Society for Information Science and Technology · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhotographyVisual researchScholarshipDisciplineSection (typography)Space (punctuation)Field (mathematics)Visual artsSociologyComputer scienceInformation scienceData scienceLibrary scienceSocial scienceArt

Abstract

fetched live from OpenAlex

Abstract This methods‐oriented paper introduces visual methods and specifically photography to study immediate information space (Lee, 2003 ); that is, information‐rich settings such as offices or homes. It draws upon the authors' firsthand ethnographic field experiences, a review of relevant theoretical and methodological literature, and an analysis of cases within information studies that have made use of visual and photographic techniques. To begin, the traditions of visual research within anthropology and sociology are traced and major epistemological, methodological, and disciplinary debates associated with visual scholarship are presented. Then, investigations of immediate information space that utilize photography are analyzed, including examples from the areas of personal information management, health informatics, information behavior, and computer‐supported cooperative work. Moreover, a section entitled “Applying Photographic Techniques…” supplies guidelines for employing photography in a research design, as well as a question‐based research framework and tips for photographing information phenomena.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.004
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.318
GPT teacher head0.510
Teacher spread0.191 · 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