Humor and laughter, playfulness and cheerfulness : upsides and downsides to a life of lightness
Notice bibliographique
Résumé
This research topic brings together the four research areas of humor, laughter, playfulness, and cheerfulness. There are partial overlaps among these phenomena. Humor may lead to laughter but not all laughter is related to humor. Playfulness is considered the basis of humor (a play with ideas), but not all play is humorous. Cheerfulness is considered the temperamental basis of good humor, a disposition for laughter and for keeping humor in face of adversity but it mostly overlaps with the socio-affective component of humor. Laughter was considered a play signal and to indicate the annulment of seriousness, but there is play without laughter and laughter outside of play. Cheerfulness might facilitate play and cheerful state might be raised due to play but again the conceptual overlap is only partial. They all contribute to levity in life and their apparent similarity suggests studying them together to map out the territory; i.e., to see where they overlap and what is specific. While these traits and behaviors have the potential to contribute to a good life, there is the danger of overlooking their non-virtuous facets; that is, laughter may not only be expressing amusement but scorn directed at people, humor may be benevolent but there is also sarcasm, and playfulness may elicit positive emotions but also risk prone behaviors. While this research topic solicited articles to these four domains without the aim to connect them, a few articles did and it is expected that growing together will be one outcome of this compilation of articles. Currently, these fields are studied mostly in isolation. A literature search (using the psychology database of Web of Science Core Collection from 1900, 06.08.2018) yielded that humor is clearly leading in terms of number of publications (n = 3,006), followed by laughter (n = 1,412), playful(ness) (n = 629), and cheerful(ness) (n = 204). As a comparison, antonyms were studied as well, and yielded higher numbers, such as for crying (n = 1640), serious-mindedness (or seriousness) (n = 892), and sadness (n = 3,654). The latter indicates that sadness is 18 times more frequently researched than cheerfulness. Next, the frequency of articles combining terms was investigated. Combinations of humor and one of the other key terms are rather infrequent with the exception of “humor and laughter” (n = 454), suggesting that about 10% of all articles on humor also refer to laughter. Humor and playfulness (n = 59) and humor and cheerfulness (n = 53) represent only 2% of all articles on humor, and these numbers are still much higher than any combination among the other three. This clearly shows that work is needed integrating these areas to examine how the concepts overlap both regarding their defining substance but also in predicting third variables. It should be mentioned that in a pioneering publication preceding the renaissance of empirical humor research three of the keywords were considered together. Toronto-based English psychologist (Berlyne, 1969) gave an account of laughter, humor, and play in a chapter in a handbook of social psychology. The compilation of research in the four fields is aimed at deepening our understanding of these concepts and stimulating research combining them.
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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,004 | 0,001 |
| Bibliométrie | 0,017 | 0,017 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».