Centering the White Gaze: Identity Construction among Second-Generation Jamaicans and Portuguese
Bibliographic record
Abstract
This article examines identity construction among second-generation Jamaicans and Portuguese in Toronto. The research question guiding this study is as follows: in a "multicultural" Canadian setting, are there differences between the ways second-generation diasporic Jamaicans and Portuguese define themselves, both ethnically and racially, and how others see them? To address this line of inquiry, I conducted 43 in-depth interviews with second-generation Jamaicans and Portuguese in the Greater Toronto Area (GTA). This study also seeks to lay bare the impact of racialization on identity construction. Since both the Jamaican and Portuguese participants of this study are mostly working-class immigrants for whom class is defined through a neo-Marxist lens, it is easier to discern the impact of race on identity construction when the role of class is held constant. Furthermore, comparison of the two groups is utilized to delineate distinct degrees of racialization within the two groups: one is a "visible" minority while the other is a non-visible minority. Based upon my interviews and my review of the literature, I argue that Portuguese are seen as dark-whites in Toronto due to their social class and their non-Anglo-Saxon culture. On the part of Jamaicans, society in general defines Jamaicans as black as a result of slavery, power relationships, and color symbolism.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".