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Record W4249698141 · doi:10.32920/ryerson.14655099

A Rhetorical Discourse Analysis of the Student Facebook Group UWO Students Against Israel Apartheid Week

2021· preprint· en· W4249698141 on OpenAlexaff
Jessica Ringel

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRhetorical questionRhetoricIdeologyPoliticsSociologyRhetorical deviceSocial mediaMedia studiesDiscourse analysisSocial psychologyPsychologyPolitical sciencePublic relationsLinguisticsLawLiteratureArt

Abstract

fetched live from OpenAlex

This MRP will examine the use of rhetorical strategies in an online political discussion group. The Rhetoric of Social Intervention (RSI) model will be used to perform a rhetorical and textual discourse analysis of the comments that users post in the Facebook group Each element of the RSI model (attention, power, need) helps group members to communicate their message through a persuasive approach, possibly leading to the enactment of some type of online or offline political change. Israel Apartheid Week (IAW) is a valuable case study because this annual event occurs in an attempt to instill the ideology that global society should view Israel as an apartheid state. Since ideology and rhetoric form the underpinnings of the RSI model, this lens is relevant to evaluating the use of rhetorical strategies within this particular group. The rhetorical dimensions of online discourse must be further explored in order to provide a more comprehensive understanding of the role of online political communication within a digital era.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0060.004
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.058
GPT teacher head0.411
Teacher spread0.353 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2021
Admission routes1
Has abstractyes

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