Comparison of Fatal Recreational Drug Overdoses between Celebrities and Non-Celebrities
Notice bibliographique
Résumé
Previous studies have examined drug overdoses among celebrities, but not in comparison to the general population. This study’s goal was to analyze whether celebrities have higher fatal overdose rates from recreational drug use than the non-celebrity population. It is often presumed that celebrities engage in more drug use to cope with their stressful and taxing lifestyles. To test this claim, we gathered a list of American celebrities that fatally overdosed on drugs from 1999 to 2017 (inclusive), as well as the number of overdoses in the general American population during this time frame. Certain drugs of interest were kept and less commonly occurring drugs that resulted in overdose were excluded, leaving us with opioids, heroin, cocaine, benzodiazepines, psychostimulants, and antidepressants. Descriptive statistics of both populations including gender and specific professions of celebrities were collected. Then, an independent samples t-test was used to discover if there was a significant difference between fatal overdoses for the celebrity versus non-celebrity population in general and for each drug listed previously from the years 1999 to 2017. Pearson’s correlation analysis was used to find if there was a difference in the yearly trend of overdoses for celebrities versus non-celebrities during the same time range. Descriptive statistics demonstrated that males comprised 62.9% of fatal overdoses for non-celebrities and 73.5% for celebrities, and musicians (24.3%), athletes (23.6%), and actors (17.6%) tend to overdose the most in terms of celebrity professions. In addition, the results from the t-test showed that non-celebrities had not fatally overdosed at significantly different rates than celebrities from 1999 to 2017. as well as overdosed at no significantly different rate for each individual drug than celebrities during this time frame. However, the exceptions were any opioids and benzodiazepines, for which the former group overdosed at a significantly higher rate. Pearson’s correlation analysis yielded an insignificant negative correlation between fatal overdoses and years passed between 1999 to 2017 for celebrities, and a significant positive correlation between fatal overdoses and years passed for non-celebrities. The judgmental heuristics may make us believe that more celebrities fatally overdose than non-celebrities, and that this presumption could potentially be problematic because celebrities have a massive influence on society, which could lead the general population to engage in these self-destructive behaviours themselves.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».