Antagonistic framing and the social exclusion of Rohingya in Myanmar’s parliamentary discourses (2011–2021)
Bibliographic record
Abstract
Antagonistic frames about minority groups are hard to dislodge. Their persistence limits the scope for conflict resolution in divided societies. The parliament that surfaced in Myanmar during a decade of opening (2011–2021) presents a case for studying how emerging legislators develop strategies for minority exclusion. Through a frame analysis of parliamentary discourses focused on the Rohingya communities across two legislatures, we reconstruct how lawmakers framed such a vulnerable group during plenary debates. We detected five adversarial frames deployed by lawmakers regardless of their ethnoreligious background or party affiliation: (1) denial, (2) invasion, (3) inhospitality, (4) racist othering, (5) sexualized demonization. We found a clear alignment with popular master frames deeply embedded in Myanmar society. We further argue that such antagonistic framing developed in parliament served two purposes: it delegitimized the Rohingya as an ‘outgroup’ in official discourse while seeking to homogenize the rest of society despite entrenched ethnoreligious divisions.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".