Bibliographic record
Abstract
Mainstream media reports on the rise of “nepo babies” have brought renewed attention to the advantages that famous and well-connected parents can provide. Drawing from a sample of 331 in-print and online articles, we apply a cultural frame analysis to study news media discourse around nepotism with a focus on how celebrity children are represented and whether these representations support or refute an ideology of meritocracy. We find that nepotism is often framed in one of four ways. First, and most commonly, nepotism among celebrity children is rendered defensible through allusions to hard work and sensationalized accounts of celebrities’ lives and lifestyles. Second, nepotism is objected to for the uneven privileges that celebrity parentage can provide. Third, a minority of articles contextualize privilege and produce order. The remaining frames presented a degree of indifference, which functioned to normalize nepotism. Together, most frames reinforce the American ideology of meritocracy, suggesting that hard work and talent explain the success of celebrity children, while hiding structural inequalities and the insidiousness of privilege from view.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".