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Record W4378070147 · doi:10.31542/cb.v5i1.2523

Fighting for Women, Life, Freedom Across Borders

2023· article· en· W4378070147 on OpenAlex
Mayson Dowdeswell

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCrossing Borders Student Reflections on Global Social Issues · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsMacEwan University
Fundersnot available
KeywordsTheme (computing)IslamThe InternetSample (material)Media studiesSocial mediaHackerAdvertisingSociologyPolitical sciencePsychologyLawHistoryBusinessComputer scienceComputer securityWorld Wide Web

Abstract

fetched live from OpenAlex


 
 
 This study examined internet activism displayed in TikTok videos and the sharing forms of public protest using TikTok videos regarding the 2022 Iranian protests. A content analysis of the 50 most liked videos using the advanced search “Iran protest 2022” identified eight general themes, including educational awareness, public marches/gatherings, cutting hair, miscellaneous, sports demonstrations, hacking Iranian media/ technologies, purposeful modesty law violations, and burning hijabs. The most prevalent theme of the eight was educational awareness, accounting for 50% of the total videos used in the sample. All videos included in the sample supported the protests and the symbolism provided, and no videos were found to be pro-Islamic regime.
 
 

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0160.002
Scholarly communication0.0020.000
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 head0.069
GPT teacher head0.513
Teacher spread0.444 · 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