How Relational Publics Become Scandal Audiences: Values and the construction of scandal
Bibliographic record
Abstract
We are interested in examining the process of scandal creation through the lens of the audience. Extant work tends to address either the effects of organizational scandal, or the role of the media and social control agents in scandal creation, neglecting the audience. To address this gap, we draw on the sociological concept of the relational public to explore how individual or small group assessments become widely held social evaluations among scandal audiences. We develop a three-stage model of organizational scandal creation: first, scandal entrepreneurs and the media frame an organization’s behavior as transgressive to media consumers who react within the relational publics they constitute; next, members of those relational publics judge the act in light of their values; finally, as relational publics spread their judgment to adjacent groups, they aggregate and assemble into a scandal audience, activating the scandal. Our model adds to media-centered theories of scandal construction by highlighting the role of heterogeneous audiences and their values, building a nuanced understanding of the process of social evaluation in scandal creation.
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 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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.014 | 0.046 |
| Scholarly communication | 0.024 | 0.017 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".