Labored Masculinity: Class, Gender, and the Educational Choices and Attitudes of Young Men of Portuguese Ancestry in Toronto
Bibliographic record
Abstract
Abstract. Young men of Portuguese ancestry in Toronto continue to demonstrate low levels of academic achievement. Despite much research that focuses on masculinity to understand boys’ academic underachievement and attitudes towards schooling, the few studies on Portuguese youth in Toronto have not explored a similar connection. Specifically, this qualitative study is based on one-on-one interviews with young men of Portuguese ancestry in Toronto, and explores construc-tions of working-class masculinity to better understand their attitudes and choices concerning education. In this study, masculinity is understood relationally according to Raewyn Connell’s (2005) theoretical framework on gender and masculinity. Therefore, within their narratives, many participants reflect on sexuality to make sense of masculinity for themselves and their communities. Participant narratives indicate a connection between masculinity and schooling. Specifically, participants’ individual identities and understandings of prevailing notions of masculinity in their communities inform their attitudes and choices concerning education and schooling. Throughout my analysis, I use Pierre Bourdieu’s concepts of habitus and field (1990, 1994; Bourdieu & Passeron, 1977) to explore how notions of masculinity and educational mobility generate considerable struggle and tension in participants’ lived experiences. This study reveals specific experiences and attitudes that impact academic achievement that are linked to class and masculinity, such as resistance to help-related educational resources and negative effects of educational mobility on ethnic identity and cultural cohesiveness, among others. I mobilize these data to construct and suggest the concept of educational deselection to explore how and when young men of Portuguese ancestry arrive at decisions to deselect education.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".