Evidence map›Paper›PMID 34347806›Full record

ArticlePloS one2021

Let's go fishing: A quantitative analysis of subsistence choices with a special focus on mixed economies among small-scale societies.

Virginia Ahedo, Débora Zurro, Jorge Caro, José Manuel Galán

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Virginia AhedoDepartamento de Ingeniería de Organización, Escuela Politécnica Superior, Universidad de Burgos, Burgos, Spain.ORCID 0000-0002-9812-388X
Débora ZurroDepartamento de Arqueología y Antropología, HUMANE - Human Ecology and Archaeology, Institución Milá y Fontanals de Investigación en Humanidades - Consejo Superior de Investigaciones Científicas (CSIC), Barcelona, Spain.
Jorge CaroDepartamento de Ingeniería de Organización, Escuela Politécnica Superior, Universidad de Burgos, Burgos, Spain.
José Manuel GalánDepartamento de Ingeniería de Organización, Escuela Politécnica Superior, Universidad de Burgos, Burgos, Spain.ORCID 0000-0003-3360-7602

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The transition to agriculture is regarded as a major turning point in human history. In the present contribution we propose to look at it through the lens of ethnographic data by means of a machine learning approach. More specifically, we analyse both the subsistence economies and the socioecological context of 1290 societies documented in the Ethnographic Atlas with a threefold purpose: (i) to better understand the variability and success of human economic choices; (ii) to assess the role of environmental settings in the configuration of the different subsistence economies; and (iii) to examine the relevance of fishing in the development of viable alternatives to cultivation. All data were extracted from the publicly available cross-cultural database D-PLACE. Our results suggest that not all subsistence combinations are viable, existing just a subset of successful economic choices that appear recurrently in specific ecological systems. The subsistence economies identified are classified as either primary or mixed economies in accordance with an information-entropy-based quantitative criterion that determines their degree of diversification. Remarkably, according to our results, mixed economies are not a marginal choice, as they constitute 25% of the cases in our data sample. In addition, fishing seems to be a key element in the configuration of mixed economies, as it is present across all of them.

Indexed as

EcosystemAgricultureAnimal HusbandryAnimalsAnimals, DomesticEconomicsEntropyFoodHumansMachine LearningSocieties

Identifiers

PMID34347806
PMCPMC8336859

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.