Enrico Croce, Francesco Carrer, Diego E. Angelucci
{"title":"民族考古归纳预测模型:意大利阿尔卑斯地区的实地试验","authors":"Enrico Croce, Francesco Carrer, Diego E. Angelucci","doi":"10.1007/s10816-025-09712-w","DOIUrl":null,"url":null,"abstract":"<p>Inductive predictive modelling is a controversial tool in archaeology. Visibility, taphonomy and research history can affect the statistical reliability of an archaeological dataset to be used as a training sample for a predictive model. To overcome these biases, an ethnoarchaeological approach has been proposed. This methodology has been developed and tested on a pastoral context in the Eastern Italian Alps. The present research proposes an application to a different, more composite landscape in the Central Italian Alps, testing the reliability of the model in relation to a heterogeneous and diachronic dataset, collected through extensive fieldwork. The results show that the model has an excellent degree of accuracy in predicting past structures with a similar purpose of use as the training sample. In addition, we show that its discriminative power can be greatly improved by the use of contemporary environmental predictors. However, the use of variables non-quantifiable for the past is an issue for the full applicability of this type of model to archaeological datasets. The results also show that this methodology, regardless of predictive results, can give us a good insight into the relationship between humans and their environment. The field application of the methodology has led us to understand that ethnoarchaeology can already be considered a reliable approach to address various methodological concerns of archaeological predictive modelling, but the primary purpose of such models should be seen more as explanatory rather than predictive.</p>","PeriodicalId":47725,"journal":{"name":"Journal of Archaeological Method and Theory","volume":"104 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ethnoarchaeological Inductive Predictive Model: A Field Test in the Italian Alps\",\"authors\":\"Enrico Croce, Francesco Carrer, Diego E. Angelucci\",\"doi\":\"10.1007/s10816-025-09712-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Inductive predictive modelling is a controversial tool in archaeology. Visibility, taphonomy and research history can affect the statistical reliability of an archaeological dataset to be used as a training sample for a predictive model. To overcome these biases, an ethnoarchaeological approach has been proposed. This methodology has been developed and tested on a pastoral context in the Eastern Italian Alps. The present research proposes an application to a different, more composite landscape in the Central Italian Alps, testing the reliability of the model in relation to a heterogeneous and diachronic dataset, collected through extensive fieldwork. The results show that the model has an excellent degree of accuracy in predicting past structures with a similar purpose of use as the training sample. In addition, we show that its discriminative power can be greatly improved by the use of contemporary environmental predictors. However, the use of variables non-quantifiable for the past is an issue for the full applicability of this type of model to archaeological datasets. The results also show that this methodology, regardless of predictive results, can give us a good insight into the relationship between humans and their environment. The field application of the methodology has led us to understand that ethnoarchaeology can already be considered a reliable approach to address various methodological concerns of archaeological predictive modelling, but the primary purpose of such models should be seen more as explanatory rather than predictive.</p>\",\"PeriodicalId\":47725,\"journal\":{\"name\":\"Journal of Archaeological Method and Theory\",\"volume\":\"104 1\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Archaeological Method and Theory\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.1007/s10816-025-09712-w\",\"RegionNum\":1,\"RegionCategory\":\"历史学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ANTHROPOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Archaeological Method and Theory","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1007/s10816-025-09712-w","RegionNum":1,"RegionCategory":"历史学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ANTHROPOLOGY","Score":null,"Total":0}
Ethnoarchaeological Inductive Predictive Model: A Field Test in the Italian Alps
Inductive predictive modelling is a controversial tool in archaeology. Visibility, taphonomy and research history can affect the statistical reliability of an archaeological dataset to be used as a training sample for a predictive model. To overcome these biases, an ethnoarchaeological approach has been proposed. This methodology has been developed and tested on a pastoral context in the Eastern Italian Alps. The present research proposes an application to a different, more composite landscape in the Central Italian Alps, testing the reliability of the model in relation to a heterogeneous and diachronic dataset, collected through extensive fieldwork. The results show that the model has an excellent degree of accuracy in predicting past structures with a similar purpose of use as the training sample. In addition, we show that its discriminative power can be greatly improved by the use of contemporary environmental predictors. However, the use of variables non-quantifiable for the past is an issue for the full applicability of this type of model to archaeological datasets. The results also show that this methodology, regardless of predictive results, can give us a good insight into the relationship between humans and their environment. The field application of the methodology has led us to understand that ethnoarchaeology can already be considered a reliable approach to address various methodological concerns of archaeological predictive modelling, but the primary purpose of such models should be seen more as explanatory rather than predictive.
期刊介绍:
The Journal of Archaeological Method and Theory, the leading journal in its field, presents original articles that address method- or theory-focused issues of current archaeological interest and represent significant explorations on the cutting edge of the discipline. The journal also welcomes topical syntheses that critically assess and integrate research on a specific subject in archaeological method or theory, as well as examinations of the history of archaeology. Written by experts, the articles benefit an international audience of archaeologists, students of archaeology, and practitioners of closely related disciplines. Specific topics covered in recent issues include: the use of nitche construction theory in archaeology, new developments in the use of soil chemistry in archaeological interpretation, and a model for the prehistoric development of clothing. The Journal''s distinguished Editorial Board includes archaeologists with worldwide archaeological knowledge (the Americas, Asia and the Pacific, Europe, and Africa), and expertise in a wide range of methodological and theoretical issues. Rated ''A'' in the European Reference Index for the Humanities (ERIH) Journal of Archaeological Method and Theory is rated ''A'' in the ERIH, a new reference index that aims to help evenly access the scientific quality of Humanities research output. For more information visit: http://www.esf.org/research-areas/humanities/activities/research-infrastructures.html Rated ''A'' in the Australian Research Council Humanities and Creative Arts Journal List. For more information, visit: http://www.arc.gov.au/era/journal_list_dev.htm