Capital accrual through post-secondary decision-making in the Canadian Modern Orthodox Jewish Community
Bibliographic record
Abstract
This qualitative study explores how cultural, social, and ethnic capital shape access to higher education for Canadian Jewish Modern Orthodox high school graduates. Using semi-structured interviews, my participants included 24 former graduates of Canadian Modern Orthodox Hebrew Academy in Southern Ontario, graduating between the years 2015–2024. Drawing on Bourdieu’s (1986) theories of cultural and social capital and Modood’s (2004) theory of ethnic capital, the study analyzes how young adults from a close-knit community navigate decisions about reputation, marriage, and career, leading to the proposed theory of aspiration capital. Building on previous models of higher education decision-making, including those by Hossler and Gallagher (1987), Perna (2006), Ross (2010), and Iloh (2018), this paper introduces the community capital cultivation model to deepen the analysis. The model reflects two basic types of students: capital cultivators and capital yearners to reflect how, even within specific ethnic communities, there are vast differences in socioeconomic status (SES) and differing higher education pathway options available to these different groups. Community aspiration (Appadurai, 2004; Gale & Parker, 2015) helps to bridge this gap by improving knowledge of pathways and subsequent capital accrual through informed higher education decision-making. Based on over nine years of teaching experience at a Canadian Modern Orthodox Hebrew Academy, the study identifies three main pathways for prospective graduates, involving either: (1) taking a gap year in Israel to study at a yeshiva or seminary institution, (2) going directly to post-secondary education in North America, and (3) enlisting in the Israel Defense Forces. The paper investigates how these pathways impact students’ capital accumulation, revealing that those who choose a gap year in Israel often acquire more capital within their community compared to those who proceed directly to university or military service.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.009 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".