Bibliographic record
Abstract
This study examined Black masculinity, the representation of Black men, and by extension the Black community. Black men in North America historically have been racially targeted and profiled in employment and education (school/prison pipeline). Black masculinity scholarship has actively represented this demography through diverse scholarships. While this may be the case, the opposite is equally true; the scholarly lens does not provide the overall picture of Black men. This exploratory/descriptive qualitative Afrocentric Indigenous narrative study applied post-colonial, anti-colonial, and critical masculinity theoretical frameworks to argue that Black masculinity is implicated in epistemological violence and imperialism. The study encompassed semi-structured interviews with 10 participants (Kenyan men in Toronto), allowing for open expression of their experiences. The Kenyan story has been missing in action; that is, the Kenyan racial experiences in immigration, education, and labour remain expunged and absent. Black masculinity has not focused on accents as a racial and gendered concept of erasing Kenyan men from social and political processes. The study is framed around the limits of Black masculinity and looks at immigration, education, and labour policies in Canada and how they expel Kenyan men from the body politic. Kenyan men that were interviewed said that though they are Black they are also African based on the complex act of accent multiplier.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.043 | 0.015 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".