Evidence map›Paper›PMID 35256800›Full record

ArticleNature human behaviour2022

The cultural evolution of love in literary history.

Nicolas Baumard, Elise Huillery, Alexandre Hyafil, Lou Safra

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Article in Nature human behaviour, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  8. A step-by-step method for cultural annotation by LLMs.Frontiers in artificial intelligence · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Nicolas BaumardInstitut Jean Nicod, Département d'études cognitives, ENS, EHESS, PSL Research University, CNRS, Paris, France. nbaumard@gmail.com.ORCID http://orcid.org/0000-0002-1439-9150
Elise HuilleryLaboratoire d'Economie de Dauphine, Université Paris Dauphine, PSL Research University, Paris, France.
Alexandre HyafilCentre de Recerca Matemàtica, Bellaterra, Spain.ORCID http://orcid.org/0000-0002-0566-651X
Lou SafraInstitut Jean Nicod, Département d'études cognitives, ENS, EHESS, PSL Research University, CNRS, Paris, France.ORCID http://orcid.org/0000-0001-7618-6735

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the late nineteenth century, cultural historians have noted that the importance of love increased during the Medieval and Early Modern European period (a phenomenon that was once referred to as the emergence of 'courtly love'). However, more recent works have shown a similar increase in Chinese, Arabic, Persian, Indian and Japanese cultures. Why such a convergent evolution in very different cultures? Using qualitative and quantitative approaches, we leverage literary history and build a database of ancient literary fiction for 19 geographical areas and 77 historical periods covering 3,800 years, from the Middle Bronze Age to the Early Modern period. We first confirm that romantic elements have increased in Eurasian literary fiction over the past millennium, and that similar increases also occurred earlier, in Ancient Greece, Rome and Classical India. We then explore the ecological determinants of this increase. Consistent with hypotheses from cultural history and behavioural ecology, we show that a higher level of economic development is strongly associated with a greater incidence of love in narrative fiction (our proxy for the importance of love in a culture). To further test the causal role of economic development, we used a difference-in-difference method that exploits exogenous regional variations in economic development resulting from the adoption of the heavy plough in medieval Europe. Finally, we used probabilistic generative models to reconstruct the latent evolution of love and to assess the respective role of cultural diffusion and economic development.

Indexed as

Cultural EvolutionLoveAsian PeopleEuropeHumansWhite People

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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.