Narratology, Rhetoric, and Transitional Justice: The Function of Narrative in Redressing the Legacy of Mass Atrocities
Bibliographic record
Abstract
This doctoral dissertation, Narratology, Rhetoric, and Transitional Justice: the Function of Narrative in Redressing the Legacy of Mass Atrocities, examines the extent to which the success and feasibility of human rights tribunals and truth commissions are dependent upon the ways in which the past is narrativized in State-sponsored legal reports and subsequently promulgated through the stories we tell. Juxtaposing three historical cases that have constituted transitional justice according to divergent ideological paths, Narratology, Rhetoric, and Transitional Justice compares and cross-references the final reports on three high-profile transitional justice cases: the Nuremberg tribunals (1945-49), the Argentine Trial of the Juntas (1985), and the Canadian Truth and Reconciliation Commission (2008-15), to study the ways in which these reports have shaped the collective or national memories of various historical traumas. The dissertation examines how the final reports on truth commissions and war crimes tribunals deploy a highly sophisticated set of rhetorical and narratological techniques in order to fix a single, specific version of historical events in the cultural memories with disparate aims in bringing together a fractured nation. By highlighting the significant degree of artistry that go into preparing these reports, it examines how and why transitional governments are often motivated to frame historical violence in order to elicit collective feelings of outrage, shame, guilt, or forgiveness. Narratology, Rhetoric, and Transitional Justice thereby illustrates how transitional justice practices mobilize blueprints for reconciliation, restoration, or retribution through the recovery and narrativization of traumatic memories, and how these respective sentiments have facilitated the implementation of subsequent political and economic policies by the transitional governments. A key aspect of this analysis centeres on the unique ability of final reports to contextualize national traumas by designating precisely which crimes were committed, by and against whom, by regulating whose testimony is to be included and/or excluded from the master narrative, and by articulating the appropriate measure of justice that ought to be faced by the perpetrators. As the apotheosis of the transitional justice process, my research demonstrates that truth commission reports not only present their mercurial and highly contentious histories as binding, legally-validated, and irrefutably fixed versions of a series of often dubious events, but they also effectively situate each citizen within the victim/perpetrator and innocent/guilty binary ethical paradigms upon which the judicial system is grounded. Negotiating the final reports on truth commissions and human rights tribunals as historical non-fiction texts, these case studies weigh their reports alongside other vehicles of cultural storytelling (including historical novels, films, ballets, etc.).
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.031 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".