Bibliographic record
Abstract
Canada prides itself as a nation welcoming to immigrants, but this multicultural façade cloaks the struggles of immigrants who fight against systemic inequality. This study aims to expose the mechanisms of societal and systemic oppression faced by immigrants in Canada, especially Black immigrants, as well as the psychological isolation they endure living in the diaspora. The study relies primarily on Austin Clarke’s novel More, and investigates economic gatekeeping by Canadian employers who often require Canadian experience and education, relegating skilled migrants to unemployment and underemployment. This illustrates the barriers to upward social mobility faced by Canadian immigrants, a reality portrayed in More by the protagonist Idora’s poverty despite living for thirty years in Canada. This paper also delineates the societal oppression which manifests in the Canadian media’s perpetuation of discrimination and projection of degeneracy on Black Canadians. Furthermore, it investigates the role of unchecked police brutality in continuing psychological exclusion and brutal violence towards Black Canadians. The psychological alienation and denigration experienced by immigrants and those living in the diaspora is also explored through More. In this context, those living in the diaspora is defined by migrants and their descendants who live in one country but feel strong emotional and identity ties to their former country. Therefore, Canada’s image as haven for immigrants is dispelled through its systemic and societal prejudice and exploitation of immigrants, complicity towards acts of brutal violence conducted by police officers, and exclusion towards those living in the diaspora.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.033 | 0.019 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".