Passion as Capital: The Cultural Production of "Good Computer Scientists"
Bibliographic record
Abstract
"Do what you love" has become a hegemonic mantra in large swaths of the labour force, and the expectation for workers to be passionate about their work is intense within the technology sector. When we interviewed eight undergraduates at a large Canadian university about what makes someone a "good computer scientist," participants stressed the importance of passion. Passion was described as a form of capital: to be accumulated and traded for advancement in the labour market. We examine how passion works as a hegemonic norm within this culture, and untangle passion as requiring two distinct processes: conspicuous production (via extracurriculars and internships), and affective passion (via performing interest and enthusiasm for the subject). We explore the relationships and feedback loops amongst conspicuous production, affective passion, and other forms of Bourdieusian capital. In doing so, we uncover the mechanics of the power structures which underlie post-feminist and meritocratic narratives of self-motivated passion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".