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Record W4378070804 · doi:10.31542/cb.v5i1.2520

The Abortion Debate

2023· article· en· W4378070804 on OpenAlex
Aliza Bukhari

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
TopicLaw, Rights, and Freedoms
Canadian institutionsMacEwan University
Fundersnot available
KeywordsInjusticeBetrayalHappinessAbortionQualitative analysisPsychologyContent analysisQualitative researchSocial psychologyCriminologyPolitical scienceSociologySocial sciencePregnancy

Abstract

fetched live from OpenAlex


 
 
 This qualitative analysis investigated public reactions in response to the overturning of Roe v. Wade. This consisted of a content analysis of 50 of the most recent comments from an NBC news video posted to the TikTok account for the Today Show. The analysis identified four findings, with an emphasis on the last finding. The results demonstrated that individuals felt strongly about the overturning: 1) reactions were either for or against the decision, 2) forty-two of the comments were reactions against the overturning while 8 were for, 3) general themes found among the 8 comments were happiness, celebration, unsympathetic and dismissive, and 4) the most apparent themes among the 42 comments were freedom of choice, individual rights, injustice, medical and societal implications, emotional and betrayal.
 
 

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0240.012
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 head0.051
GPT teacher head0.475
Teacher spread0.424 · 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