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Record W2794181429 · doi:10.1002/asi.24012

Information triangulation: A complex and agentic everyday information practice

2018· article· en· W2794181429 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of the Association for Information Science and Technology · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsTriangulationAgency (philosophy)Information seekingEveryday lifeFace (sociological concept)Computer scienceInformation systemSociologyData scienceKnowledge managementEpistemologySocial scienceInformation retrievalEngineeringMathematics

Abstract

fetched live from OpenAlex

In contemporary urban settings, information seekers may face challenges assessing and making use of the large quantity of information to which they have access. Such challenges may be particularly acute when laypeople are considering specialized or technical information pertaining to topics over which knowledge is contested. Within a constructivist grounded theory study of the health information practices of 39 young parents in urban Canada, a complex practice of information triangulation was observed. Triangulation comprised an iterative process of seeking, assessment, and sense‐making, and typically resulted in a decision or action. This paper examines the emergent concept of information triangulation in everyday life, using data from the young parent study. Triangulation processes in this study could be classified as one of four types, and functioned as an exercise of agency in the face of structures of expertise and exclusion. Although triangulation has long been described and discussed as a practice among scientific researchers wishing to validate and enrich their data, it has rarely been identified as an everyday practice in information behavior research. Future investigations should consider the use of information triangulation for other types of information, including by other populations and in other areas of contested knowledge.

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)0.012
metaresearch head score (Gemma)0.030
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.021
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 head0.040
GPT teacher head0.398
Teacher spread0.358 · 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