Bibliographic record
Abstract
I welcome the opportunity to provide some reflections on Michael Yaziji's paper, Toward a Theory of Social Risk: Antecedents of Normative Delegitimation. The process of reflection allows me to review some ideas that have been fermenting in my head related to the concepts of legitimacy, reputation, corporate social performance, and corporate citizenship in the context of strategy, institutional, and stakeholder theories. Viewing social risk theory as a young but vigorously growing tree, I seek to fertilize a few more theoretical roots and graft on a few leaves and branches. This also allows me to comment on the importance of crafting a readily understandable yet thought-provoking paper. I appreciate Rodolphe Durand and Jean McGuire for asking me to participate. I was intrigued by the theme Pushing old legitimacies down the stairs. Many of my comments on the theoretical and empirical issues for research on delegitimation may echo others in this issue. For instance, I may not be alone in wondering what parts of theories of legitimation apply to theories of delegitimation and what parts of the latter are substantively different.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".