MétaCan
Menu
Back to cohort
Record W3107025682 · doi:10.1145/3428091

Online Xenophobic Behavior Amid the COVID-19 Pandemic

2020· article· en· W3107025682 on OpenAlexaff
Roy Ka-Wei Lee, Zhi Li

Bibliographic record

VenueDigital Government Research and Practice · 2020
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsXenophobiaCoronavirus disease 2019 (COVID-19)Pandemic2019-20 coronavirus outbreakModerationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Deterrence (psychology)Online and offlinePolitical scienceCriminologyPsychologyRacismSocial psychologyLawInfectious disease (medical specialty)VirologyMedicine

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has developed to be more than a bio-crisis as global news has reported a sharp rise in xenophobia and discrimination in online and offline communities. This commentary discusses the deterrence policies and automated content moderation technology to curb the spread of online xenophobic behaviors. We suggested some potential exploration areas where multiple stakeholders can come together to address the online xenophobic issues amid the COVID-19 pandemic.

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.

How this classification was reachedexpand

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly 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 score0.936
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
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 head0.187
GPT teacher head0.392
Teacher spread0.205 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueDigital Government Research and PracticeSame topicHate Speech and Cyberbullying DetectionFrench-language works237,207