MétaCan
Menu
Back to cohort

Perceptions of Identity and Expertise in Heavy Metal Fans within One Online Community of Practice

2014· book-chapter· en· W2910583985 on OpenAlex
Kathryn Urbaniak

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

VenueAdvances in social networking and online communities book series · 2014
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsConcordia University
Fundersnot available
KeywordsIdentity (music)PerceptionOnline identityEthnographyPsychologySocial psychologyOnline communityCommunity of practiceWorld Wide WebSociologyThe InternetPedagogyComputer scienceAesthetics

Abstract

fetched live from OpenAlex

Identity is central to learning (Wenger, 1998), and identity in online forums can be represented verbally in posts and comments as well as non-verbally through choices such as username, user picture, and signature. How a forum user interacts with others based on their perceptions of another users’ identity and expertise impacts their experiences. This chapter examines informal learning experiences and behaviour based on the perceptions of others for three heavy metal fans within an online forum through a cyber-ethnographic study. This study explores participants’ interactions with both verbal and non-verbal content to form their perceptions of others, including perceptions of expertise. The participants controlled how they interacted with content and other users in a Web 2.0 environment, which impacted the shared construction of knowledge based on their perceptions of identity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.469
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
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 head0.052
GPT teacher head0.375
Teacher spread0.323 · 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