SUICIDES OF FAMOUS ATHLETES OF MODERN TIME: STORIES AND REASONS
Notice bibliographique
Résumé
Introduction. Professional athletes often suffer from physical and psychological injuries, they are underconsiderable pressure due to the constant need to demonstrate their victories, the high level of competition, violations of fair play, etc. These factors can increase the risk of suicide among them.The aim of the work is to study the life, professional career, reasons and methods of suicide of famous athletes in the first quarter of the 21st century. We used general scientific (description and observation) and theoretical (analysis, synthesis, classification, explanation, and generalization) research methods to achieve the goal.Results. The present study analysed information on 336 male and 45 female athletes who committedsuicide between January 2000 and December 2024. All the data was taken from verified sources. The research demonstrated that for every instance of female athlete suicide, there were approximately nine instances of male athletes committing suicide. The highest number of male athlete suicides was recorded in 2019, the lowest in 2000, and the highest number of female athletes committed suicide in 2020. Since 2009, there has been an increase in the incidence of suicidal acts. A study revealed that male athletes were most prone to committing suicide between the ages of 30 and 49, while female athletes demonstrated a peak in suicide rates between the ages of 20 and 39. In the case of the 252 athletes whose method of suicide is known, hanging and gunshot wounds were the most prevalent. In the case of the 26 female athletes, the most prevalent underlying factors contributing to injury were found to be falls from a height and overdosesor poisoning with dangerous substances. It was not possible to ascertain the method of suicide of 84 male athletes and 19 female athletes due to an absence of relevant information.Research has identified a number of factors that have been demonstrated to increase the risk of suicide, including diseases and injuries, career development and achieved results, difficult social relationships and economic reasons. The behaviour of an athlete who is prone to cruelty, sudden mood swings, depression,and suicidal intentions always requires urgent action. In such a state, the individual’s actions can become a potential threat not only to themselves but also to their loved ones.Conclusions. In the contemporary context, the development of reliable algorithms for predicting and preventing suicide has become imperative. The identification of problems at an early stage and the prescription of appropriate treatment are of paramount importance. Furthermore, restrictions on access to firearms must be considered, along with the prevention of the transformation of suicide locations into attractive sites for the development of than atourism.
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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 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».