Capital, Power, and Habitus: How Does Bourdieu Speak to the Tenure Process in Universities?
Bibliographic record
Abstract
This paper uses sociologist Pierre Bourdieu's theory of social structure (1986, 1990a, 1990b, 1991 , 1995, 1998) to better understand the concept of tenure and the relationships that contribute to a conflicted experience for many. Social structures reproduce themselves according to the rules of the field, and various forms of social, cultural, and symbolic capital, underlined by economic capital. are traded by individuals who each have a sense of their value in the system, or habitus. Aspects of the tenure process reflect the rules of the field of academia, excluding those academics (Bonner, 2004; Connell & Savage, 2001). The process of tenure is subjective and can exclude those who are most worthy (Batterbury, 2008; Benton, 2007). A glut of professors can reinforce the status quo and challenge it (Bourdieu, 1988) . Recommendations are made to improve the inherent biases and conflicts within the process.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.045 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".