Trends in the Use of Promotional Language (Hype) in Abstracts of Successful National Institutes of Health Grant Applications, 1985-2020
Notice bibliographique
Résumé
Importance: The integrity of the grant application process is important to the success of the entire research enterprise. However, little information is available concerning the prevalence and evolution of subjective or promotional language ("hype") that has the potential to undermine objectivity in the writing and evaluation of grant applications. Objective: To assess changes over time in the use of hype in abstracts of National Institutes of Health (NIH) grant applications. Design, Setting, and Participants: This cross-sectional study assessed the prevalence of promotional adjectives in abstracts in the NIH archive from 1985 to 2020. Main Outcomes and Measures: From all abstracts in the NIH RePORTER (Research Portfolio Online Reporting Tools: Expenditures and Results) archive, adjectives were automatically extracted, and their frequencies in the most recent year (2020) were assessed relative to the start year (1985). Adjectives that shifted significantly in frequency and that carried a promotional sense (ie, hype) were retained, and patterns of change were assessed by plotting yearly frequencies (1985-2020). By grouping the adjectives based on shared semantic properties, broad meanings commonly expressed by hype were identified. Absolute change was measured as the difference in normalized frequency between 1985 and 2020. Relative change was measured as the percentage change in normalized frequency in 2020 relative to 1985, or the first year of occurrence. Results: In total, 901 717 abstracts were analyzed and 139 adjective forms were identified as hype. Among these 139 adjective forms, 130 hype adjectives increased in frequency by 7690 words per million (wpm) (mean [SD] relative increase, 1378% [3132%]), while 9 hype adjectives decreased in frequency by 686 wpm (mean [SD] relative decrease, 44% [18%]). The largest absolute increases were for the terms novel (1054 wpm), critical (555 wpm), and key (461 wpm), while the largest relative increases were for the terms sustainable (25 157%), actionable (16 114%), and scalable (13 029%). Hype most often serves to promote the significance, novelty, scale, and rigor of a project; the utility of the expected outcomes; the qualities of the investigators and research environment; and the gravity of the problem; as well as conveying the personal attitudes of the applicants. Conclusions and Relevance: Levels of hype in successful NIH grant applications have increased over time from 1985 to 2020. The findings in this study should serve to sensitize applicants, reviewers, and funding agencies to the increasing prevalence of subjective, promotional language in funding applications.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».