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Record W2601242081 · doi:10.1080/17439884.2017.1305966

Scholars in an increasingly open and digital world: imagined audiences and their impact on scholars’ online participation

2017· article· en· W2601242081 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLearning Media and Technology · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of British ColumbiaRoyal Roads University
FundersCanada Research Chairs
KeywordsPresentation (obstetrics)Media studiesSociologySocial mediaContext (archaeology)Affect (linguistics)Digital mediaPublic relationsPolitical scienceHistory

Abstract

fetched live from OpenAlex

This study investigates the audiences that scholars imagine encountering online and the ways in which these audiences impact scholars’ online participation and presentation of self. Prior research suggests that imagined audiences affect what users share and how they present themselves on social media, but little research has examined this topic in the context of faculty members and doctoral students (i.e., scholars). An analysis of interviews with 16 scholars shows that imagined audiences span the personal–professional continuum. Further, most scholars imagined their online audiences as known and familiar. Though many recognized collapsed contexts as problematic, several others appeared more comfortable with audience collapse than prior literature suggests. Findings also suggest that scholars’ conceptualizations of their audiences differ from those of their universities, principally in that scholars imagine their audiences as communities rather than as venues for attracting professional attention.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.040
GPT teacher head0.390
Teacher spread0.351 · 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