Notice bibliographique
Résumé
Paper presented at the ISTP Conference, Toronto 2007. Mate choice, courting, parental investment, attractiveness, and love are a few examples of human interactions in which evolutionary psychology has a keen interest. Theories like this shed light on human partner preferences and there is quite strong empirical support for that as well. Roughly the general version says that \n \nFor any member of the sexes, if the individual is interested in long-term mating, it will select a mate that is showing to be \n1.\table to invest in the relationship and in their offspring \n2.\twilling to invest in the relationship and in their offspring \n3.\table to physically protect self, partner and offspring \n4.\thaving good parenting skills \n5.\tcompatible with the self (has similar values, age, personality etc.) \n \nThese studies show how the preferences in partner selection resemble each other. Over many countries and cultures, within and between the sexes, within and between age groups, social economic classes etc. people all are, to certain extend alike in what they like and dislike. The interpretation of what is alike, however, is a matter of debate. That is, “resemblance” always is resemblance in the eye of the persons or organisms that compare. \n \nSo a preference for a certain body shape, for symmetry, for sharp male facial contours and soft contours in the female face, for a particular waist-hip ratio etc. is in the eye of the beholder. That is, in the eye of the organism involved, or at least in the eye of the sex of the organism involved, or at least in the eye of the members of a certain age, culture, historical period of the sex of the organism involved, or at least…etc. \n \nFrom another angle there are studies of how personal knowledge of the human body partially accounts for the experience of romantic love in humans. Helen Fisher’s work is an example. Focusing on the experiences of human beings concerning romantic love, she reports remarkable regularities in and resemblances of feelings between human beings from different countries, cultures, ages, the sexes and even, apparently, between non-human animals – primates, and some other mammals in particular. What is remarkable here is that they mostly report of either internal feelings or the bilateral meaningful behavior and expected or hoped for behavior of the one in love and the one loved.From yet one other angle, Antonio Damasio’s theory on emotions and feelings also seems to enhance evolutionary psychology’s claims. Damasio suggests that vision, hearing, touch, taste and smell result from nerve activation patterns that reflect states of the external world. Emotions, on the other hand, are nerve activation patterns that correspond to the state of the internal world. The experience of sexual attraction is activated but also recorded in nerve cell activation patterns obtained by the brain from neural and hormonal feedback, and is experienced as a body state.Briefly, we argue, the way we interpret or represent our feelings, depends on how feelings are stylized, articulated, and expressed in communities. From (socially) skilled members of the group we learn how to appropriately deal with affects.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 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 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 ».