Beyond truth: materialist approaches to reconciliation theories and politics in Canada
Bibliographic record
Abstract
In the last decade, reconciliation, apology, and forgiveness have become omnipresent forces in the international political sphere. Since the Nuremberg trials, strict retribution is no longer the responsible method for dealing with atrocity. Reconciliation offers conflict resolution that redresses historical injustice by appealing to reparative models of justice aimed at healing the rifts between victims and perpetrators. In 2006, Canada became the latest country to adopt a state-sponsored process of reconciliation. The Canadian Truth and Reconciliation Commission (TRC) was established to “contribute to truth, healing and reconciliation” (“Schedule ‘N’”, 1) between Native and non-Native groups in Canada. This dissertation maps out the history of reconciliation as it is connected to Canada and identifies the ways in which the TRC facilitates and confounds conflict resolution in a colonial state. By critically analysing contemporary literature, film, politics and social movements, my dissertation develops a materialist approach to reconciliation via the ideas of “the call,” apology, reparation and forgiveness, applying these ideas to the lived experience (emotional, political, financial) that individuals and communities have to contend with in the reconciliatory process. In this dissertation I argue against those who suggest that the emergence of reconciliation in the modern era indicates that the international community is “returning to harmony” (Wagamese 134). As opposed to defining it as an indicator of burgeoning ethical politics, I suggest that “reconciliation,” particularly in how it is being articulated in settler states, is being deployed as a means to close off difference and contradiction and facilitate self-interest. As such, reconciliation must be approached as an ideological instrument rather than as “a potentially new international morality” (Barkan ix).
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.044 | 0.098 |
| Scholarly communication | 0.024 | 0.010 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".