ISO Certificates as Organizational Degrees? Beyond the Rational Myths of the Certification Process
Bibliographic record
Abstract
This paper explores both the concrete and symbolic aspects of how ISO 9000 certification audits are prepared for and passed. Based on interviews with 60 respondents employed in certified organizations, this study analyzes the process of preparing for and passing an ISO certification audit through the lens of the degree-purchasing syndrome (DPS) in education, which refers to the disconnect between the acquisition of academic degrees and the learning process they should entail. This perspective makes it possible to go beyond the neo-institutional approach to shed light on the scholastic, ethical and contradictory aspects of the ISO certification process, which remain largely unexplored in the literature. The findings debunk the rhetoric of impartiality, objectivity and rigor surrounding the ISO certification process. They also reveal the tendency to acquire ISO certification as a sort of “organizational degree” after passing a quite predictable exam, with all the pitfalls that entails, such as rote preparation, procrastination, short-term focus and cheating.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.039 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".