An archaeologist’s view: Knowing the data. A commentary on Keigley (2019) and Beschta and Ripple (2019)

Cannon, Kenneth P.; Cannon, Molly Boeka; Martin, Houston

doi:10.1016/j.rala.2020.04.006

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…These totals exclude sessions excluded due to poor-quality responses. To determine whether a session should be excluded, we followed practices described by Cannon (2019). Specifically, we calculated a “trouble score” for each rater based on different concerns about rating qualities (see Supplemental Appendix C), and we dropped raters with trouble scores of two or more (13 of 188).…”

Section: Studymentioning

confidence: 99%

Word Embeddings Reveal How Fundamental Sentiments Structure Natural Language

Loon

Freese

2022

American Behavioral Scientist

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Central to affect control theory are culturally shared meanings of concepts. That these sentiments overlap among members of a culture presumably reflects their roots in the language use that members observe. Yet, the degree to which the affective meaning of a concept is encoded in the way linguistic representations of that concept are used in everyday symbolic exchange has yet to be demonstrated. The question has methodological as well as theoretical significance for affect control theory, as language may provide an unobtrusive, behavioral method of obtaining EPA ratings complementary to those heretofore obtained via questionnaires. We pursue a series of studies that evaluate whether tools from machine learning and computational linguistics can capture the fundamental affective meaning of concepts from large text corpora. We develop an algorithm that uses word embeddings to predict EPA profiles available from a recent EPA dictionary derived from traditional questionnaires, as well as novel concepts collected using an open-source web app we have developed. Across both a held-out portion of the available data as well as the novel data, our best predictions correlate with survey-based measures of the E, P, and A ratings of concepts at a magnitude greater than 0.85, 0.8, and 0.75 respectively.

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Section: Studymentioning

confidence: 99%

Word Embeddings Reveal How Fundamental Sentiments Structure Natural Language

Loon

Freese

2022

American Behavioral Scientist

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‘Emptying Forests?’ Conservation Implications of Past Human–Primate Interactions

Amano

Wang

Boivin

et al. 2021

Trends in Ecology & Evolution

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Drivelines, hunting blinds, effigies and intercept hunting strategies in the Greater Yellowstone Ecosystem, USA

Lee

Neeley

Horton

et al. 2019

Hunter Gatherer Research

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This paper shares a description of cairn lines and hunting blinds in association with an ice patch in the Greater yellowstone Ecosystem. Until now no definitive stone features, including drivelines and hunting blinds, have been reported in association with Greater yellowstone Ecosystem ice patches; however, such features are known from ice patches in northern North America, eg yukon Territory. In the system reported here, the ice patch is presumed to be an animal attractant with the drivelines and blinds positioned to serve as intercepts. The paper also shares a brief report of a stone effigy of a probable bighorn sheep that appears to be associated with an ice patch. Such features are emblematic of spiritual provisioning in the alpine.

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An archaeologist’s view: Knowing the data. A commentary on Keigley (2019) and Beschta and Ripple (2019)

Cited by 3 publications

References 15 publications

Word Embeddings Reveal How Fundamental Sentiments Structure Natural Language

Word Embeddings Reveal How Fundamental Sentiments Structure Natural Language

‘Emptying Forests?’ Conservation Implications of Past Human–Primate Interactions

Drivelines, hunting blinds, effigies and intercept hunting strategies in the Greater Yellowstone Ecosystem, USA

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