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Record W1525222524 · doi:10.21432/t2w02t

Virtual Ethnography: Interactive Interviewing Online as Method

2008· article· en· W1525222524 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInterviewThe InternetEthnographyContext (archaeology)SociologyEducational technologyScope (computer science)Online discussionSocial constructivismPedagogyPsychologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Recognizing the power of the Internet to connect people, regardless of place or time, we explore the notion of a virtual form of ethnography, suggesting online, textual interactive interviews are worthy of research consideration. This paper reports on three research projects, drawing examples from almost ten years in the evolution of Internet supported conferencing software. It is the position of this paper that we were able to share and develop new insights into being authors, interlocutors, online learners, online researchers, and members of an educational context. Further, we feel that we were able to sustain conversations beyond the scope of many traditional face-to-face interview sessions, noting that the participants enjoyed the process and often found it hard to quit their interactions with us. Hence our position that even though the technology is still emerging and improving, the potential is clearly rich, inviting, and worth continued study.nstructor if given the authority in a social constructivist learning 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.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.338
Teacher spread0.308 · 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