Classed, raced, and gendered biographies: young people's understandings of social structures in a boomtown
Bibliographic record
Abstract
As young people attempt to adapt to a rapidly changing society, how they experience school and work has undergone significant changes in recent decades. Youth researchers attempting to understand these changes have drawn heavily on the concepts of agency and structure. In the process, researchers often end up taking a ‘middle-ground’ approach and in turn have critiqued the theorizing of Ulrich Beck for being too focused on agency. This article engages with this debate by examining young people's understandings of the social structures shaping their lives within the constantly changing environment of a boomtown. Drawing on qualitative in-depth interviews with high school students, post-secondary students, and young workers, it was found that most young people were able to recognize how class had shaped their lives, only Aboriginal young people discussed how race/ethnicity had shaped their lives, and only young women understood how gender had shaped their lives. The findings suggest that the specific local context that young people experience their school and work lives within is important in their reflexive understandings of their biographies. In this case, the boomtown environment helped to highlight difference and make only certain social structures visible to particular young people.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".