Bibliographic record
Abstract
Using Bourdieu’s theory of different types of capital and social “fields,” this paper analyzes one curriculum model, the ESL Co-op program, which is designed to meet the needs of immigrant adolescents who are primarily dependent on their first language. The program couples instruction in English as a second language (ESL) with work experience. ESL Co-op is offered in two secondary schools in a suburban Vancouver school district that is the most rapidly growing district in British Columbia. More than 30 percent of the approximately 50,000 students enrolled in the district speak a language other than, or in addition to, English in the home.A collaborative team of university researchers and district curriculum consultants inquired into the program’s success in helping recent immigrant students become aware of possible future career and job opportunities and any other aspects of the program’s operation deemed salient by the interviewees. We wondered if the folk theory of success embedded in federal, provincial, and district policy discourse, which emphasizes work experience, was in fact setting the stage for educational and occupational success of these young people.Interviews with 44 parents, 43 students, and six staff members from a total of 10 different language backgrounds revealed that staff perceive the program as a unique opportunity for students to gain exposure to Canadian work environments and to develop survival, language, and job-related skills or, in Bourdieu’s terms, embodied capital. Students’ and parents’ overriding concern is that the program precludes the possibility of graduation with the grade-12 diploma (institutional capital) available from the mainstream program.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.662 | 0.468 |
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".