Do Men and Women Report Their Sexual Partnerships Differently? Evidence from Kisumu, Kenya
Notice bibliographique
Résumé
At least two other explanations for such gender differences are plausible.First, differences may stem from sample selection bias, which may occur if, on average, men have more sexual partners outside the study area than do women, have partners younger than the minimum age of sample respondents (typically age 15 or 18) or have partners, such as commercial sex workers, who are not likely to be interviewed in standard surveys.These types of bias would tend to inflate aggregate gender differences in both the average number of partners and other reported sexual behaviors, such as condom use, frequency of sex and relationship duration.To limit the effects of sample selection bias, one study in Tanzania attempted to interview all men and women of reproductive age in four villages and restricted their sample of partners to those who resided in these villages and were the same age as the respondents (aged 15-64).5 Unfortunately, since only 84% of eligible women and 77% of eligible men participated in the survey, the investigators could not entirely eliminate the potential for sample selection effects.Nonetheless, they found that, on average, women reported significantly fewer nonmarital sexual partners than men, as well as longer sexual relationships, leading them to conclude that in general men "swagger" (i.e., exaggerate their sexual activities), while women are Do Men and Women Report Their Sexual Partnerships Differently? Evidence from Kisumu, KenyaCONTEXT: It is generally believed that men and women misreport their sexual behaviors, which undermines the ability of researchers, program designers and health care providers to assess whether these behaviors compromise individuals' sexual and reproductive health. METHODS:Data on 1,299 recent sexual partnerships were collected in a 2007 survey of 1,275 men and women aged 18-24 and living in Kisumu, Kenya.Chi-square and t tests were used to examine how sample selection bias and selective partnership reporting may result in gender differences in reported sexual behaviors.Correlation coefficients and kappa statistics were calculated in further analysis of a sample of 280 matched marital and nonmarital couples to assess agreement on reported behaviors.RESULTS: Even after adjustment for sample selection bias, men reported twice as many partnerships as women (0.5 vs. 0.2), as well as more casual partnerships.However, when selective reporting was controlled for, aggregate gender differences in sexual behaviors almost entirely disappeared.In the matched-couples sample, men and women exhibited moderate to substantial levels of agreement for most relationship characteristics and behaviors, including type of relationship, frequency of sex and condom use.Finally, men and women tended to agree about whether men had other nonmarital partners, but disagreed about women's nonmarital partners. CONCLUSIONS: Both sample selection bias and selective partnership reporting can influence the level of agreement between men's and women's reports of sexual behaviors. Although men report more casual partners than do women, accounts of sexual behavior within reported relationships are generally reliable.
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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 | 0,004 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».