So sánh phương pháp

	Smith's Salience Index (S)	Cultural Domain Analysis
Lĩnh vực	Anthropology	Anthropology
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1993	1994
Người khởi xướng	J. Jerome Smith; popularized through ANTHROPAC (Borgatti) and AnthroTools	Stephen P. Borgatti (synthesis of cognitive anthropology methods)
Loại	Salience statistic combining mention frequency and recall order in free-list data	Integrated framework for eliciting and analyzing cultural domains
Công trình gốc	Bernard, H. R. (2017). Research Methods in Anthropology: Qualitative and Quantitative Approaches (6th ed.). Lanham, MD: Rowman & Littlefield. ISBN: 9780759112421	Borgatti, S. P. (1994). Cultural domain analysis. Journal of Quantitative Anthropology, 4(4), 261–278.
Tên gọi khác	Smith's S, Salience Index S, Free-List Salience, Item Salience Score	CDA, Domain Analysis (cognitive anthropology), Cultural Domains Approach, Cognitive Domain Analysis
Liên quan	4	4
Tóm tắt	Smith's salience index, conventionally written S, is the standard statistic for summarizing free-list data: for each item it combines how many informants mentioned the item with how early the item appeared in their lists. Within a single list each item receives a local salience equal to the number of items below it divided by the list length, so the first item scores highest and the last scores lowest; S is then the average of that local salience across the entire sample, counting zero for informants who never listed the item. The result is a single per-item number that ranks the items of a cultural domain by their joint frequency-and-priority prominence.	Cultural domain analysis is the integrated framework in cognitive anthropology for discovering the content and structure of a cultural domain — a coherent set of related items such as illnesses, animals, kin terms, or emotions — as the members of a culture themselves organize it. It chains together elicitation methods (free listing, pile sorting, triad tests) and analytic methods (salience, multidimensional scaling, clustering, consensus analysis) to move from 'what items are in this domain?' to 'how are they organized and how widely is that organization shared?'