隣人格差の分析における名前に基づく人種構成の重要性
1University of Wisconsin-Madison, 1180 Observatory Drive, Madison, WI 53706, USA.
まとめ
名前を使って近所の不平等を分析すると 伝統的な人種分類よりも深い社会経済的格差が明らかになります 名前に基づく人種的構成は 劣勢のより正確な尺度を提供します
科学分野:
- 社会学
- 都市研究
- 人種不平等に関する研究
背景:
- 現代社会学では 人種的なカテゴリーを超えて 不平等を分析する必要があります
- 地域レベルでの探索は限られているが,主として個人レベルに焦点を当てている.
- 地域特性を理解する際の 人種特性の有用性は まだ十分に研究されていない.
研究 の 目的:
- 人種を代表する名前について調べる
- 名前と近所の社会経済的な特徴の関連性を調べる
- 名前に基づく人種構成が 伝統的な指標と比較して 近所の不平等をより微妙に理解できるかどうかを判断する.
主な方法:
- 3億人以上のアメリカ人の名前を含む 大量のデータセットの分析
- 名前に基づく人種構成と,従来の調査に基づく人種構成の指標を用いた社会経済的格差の比較.
- 定数的な人種構成によって定義される近隣地域における社会経済的不平等に対する命名パターンの予測力に関する検討.
主要な成果:
- 名前に基づく人種構成は 従来の指標よりも近所の社会経済的格差を より包括的に説明します
- "ブラック・サウンド"の名前が多い地区は,黒人住民の自己認識が高い地域よりも社会経済的に不利な状況にある.
- 命名パターンは,名目上の人種差が最小である場合でも,主に"黒人の名前"と"白人の名前"の2つの近隣の社会経済的不平等の変動を説明します.
結論:
- 名前から派生した人種間の類別的測定は 近隣の不平等を分析するための重要な予測力を提供します
- 名前に反映されているような 人種的典型性は,近所レベルでの社会経済的格差を理解する上で重要な要因です.
- このアプローチは伝統的な人種構成の指標を強化し 不平等のより細かい見方を提供します
関連する概念動画
Stereotypes, Prejudice, and Discrimination
91.4K
Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
91.4K
Relationship Formation
41.0K
What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
41.0K
In- and Out-Groups
39.9K
People all belong to a gender, race, age, and social economic group. These groups provide a powerful source of our identity and self-esteem (Tajfel & Turner, 1979) and serve as our in-groups. An in-group is a group that we identify with or see ourselves as belonging to.
39.9K
The Representativeness Heuristic
16.2K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
16.2K
Ranks
286
Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
286
Sign Test for Nominal Data
152
The sign test is a nonparametric method used to evaluate hypotheses about the median of a single sample or to compare the medians of two related samples. The sign test is particularly useful when dealing with nominal data, which includes distinct categories without an inherent order, such as names, labels, and preferences. Nominal data restricts statistical analysis to evaluating population proportions rather than mean or median values that require continuous data.
For example, consider a...
For example, consider a...
152


