Constructing Rwandan Identity in the Diaspora:\tRemembering the Green Hills in Cold Canada
Bibliographic record
Abstract
This study investigated the processes of identity formation among those who identified as Rwandan and lived in the Greater Toronto Area. The study was conducted using in-depth qualitative interviews and ethnographic participant observation. It argues that those who identified as Rwandan in the GTA were subject to powerful discourses of simultaneous belonging and non-belonging in both the Canadian and the Rwandan state. The extreme violence of the Rwandan genocide ruptured the bonds of belonging that had tied those who identified as Rwandan to each other and to the Rwandan state. Since 1994, the new Rwandan state had developed a powerful mythico-history that proposed that all those who are identified as Hutu are perpetual perpetrators and all those who are identified as Tutsi are perpetual victims, even as it had denied that the identities of Hutu and Tutsi continued to exist. The re-telling and re-enacting of this mythico-history became the condition of belonging to the newly created diaspora and the Rwandan state. Simultaneously, ambivalent welcome and racialization that those who identified as Rwandan faced in Canada, and, specifically, the GTA, generated an anxiety and an awareness that they could only partially belong in the new homeland. Thus, the exclusion of the Canadian state generated a desire for the imagined homeland and enabled the Rwandan state to create a diaspora. Yet, those who were defined as part of the Rwandan diaspora negotiated and navigated the terms of their belonging/non-belonging in both Canada and in Rwanda. Even as they were they were racialized by the Canadian state and framed as both desirable and threatening by the Rwandan state, those who identified as Rwandan in the GTA built a sense of home and belonging in Canada. They simultaneously became a diaspora and rooted themselves in the new homeland of Canada.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.047 | 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 teacher head, 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".