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Record W3192697815 · doi:10.1177/20563051211035356

Zoombombing During a Global Pandemic

2021· article· en· W3192697815 on OpenAlex
Greg Elmer, Stephen J. Neville, Anthony Burton, Sabrina Ward-Kimola

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

VenueSocial Media + Society · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsSimon Fraser UniversityYork UniversityToronto Metropolitan University
Fundersnot available
KeywordsPhenomenonPandemicHarassmentThe InternetSociologyCoronavirus disease 2019 (COVID-19)Public relationsCultural phenomenonPolitical scienceMedia studiesSocial scienceLawEpistemologyComputer scienceMedicineWorld Wide Web

Abstract

fetched live from OpenAlex

Using a digital methods analysis, the following article conducts a cross-platform study of the emergent “Zoombombing” phenomenon alongside COVID-19 and the concomitant on-lining of professional and public life. This empirical study seeks to provide further insight to media frames characterizing Zoombombing at the outbreak of the pandemic, providing further insight into Zoombombing as a practice, how related actions act as an extension of longer histories and practices of online harassment, and the role that various platforms play in the phenomenon’s unfolding. By interrogating these points of departure, our study sheds light not only on Zoombombing as a cultural practice, but also how these acts manifest within and across a range of Internet platforms.

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)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.052
GPT teacher head0.330
Teacher spread0.278 · 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