Frames as Boundaries: Rhetorical Framing Analysis and the Confines of Public Discourse in Online News Coverage of Vegan Parenting
Bibliographic record
Abstract
This article examines the boundary work of frames and the methodological significance of understanding this work when conducting rhetorical framing analysis. While the boundary properties of frames have been theorized by scholars, there remains a lack of clear engagement with how to effectively address these discursive boundaries methodically. I argue that agenda-dismissal, which makes use of both prolepses and blind spots, ought to be addressed in addition to agenda-setting and agenda-extension when conducting rhetorical framing analysis. A case study is provided in which the rhetorical framing of vegan parenting in online news media is analyzed and critiqued for confining the issue within a dominant health-based frame. Strategies for dismantling discursive boundaries and reframing public issues are also considered within the context of the case study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.010 | 0.041 |
| Scholarly communication | 0.018 | 0.023 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".