Revisiting credentialism – why qualifications matter: a theoretical exploration
Bibliographic record
Abstract
This article extends social realist theorising about theoretical knowledge and curriculum within the sociology of education to explore the nature of qualifications. The article draws on Bernstein’s concept of evaluative rules to do so. It evaluates human capital, institutional, and credentialist theories about the role qualifications play in society. Each offers important insights, yet each is unsatisfactory. Each fails to recognise education as a relatively autonomous field distinct from other social fields. We theorise qualifications to explore, on the one hand, the role they play in transforming society, and on the other, the role they play in reproducing social inequalities. We argue that qualifications matter, even if they are imperfect, contribute to the reproduction of social inequalities, and should be tied less, and not more, tightly to the labour market. A socially just model of qualifications would include four key purposes: individual, educational, occupational, and social.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.041 |
| Scholarly communication | 0.007 | 0.016 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".