Evidence map›Paper›PMID 34658674›Full record

ArticleThe quarterly journal of economics2021

Folklore.

Stelios Michalopoulos, Melanie Meng Xue

Open access · bronzeAbstract read
In one paragraph

Article in The quarterly journal of economics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
45.3field-weighted citation impact, top 1% of its field
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

4 citing papers in PubMed, 130 citations in OpenAlex.

  1. Article
  2. Article
  3. Persistence of gender biases in Europe.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  4. Stories in Action.Psychological science in the public interest : a journal of the American Psychological Society · 2022
    Article
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

2 authors at 2 institutions in 2 countries.

Stelios MichalopoulosBrown University, Center for Economic Policy and Research, and National Bureau of Economic Research, United States.
Melanie Meng XueNew York University, Abu Dhabi and London School of Economics, United Kingdom.
National Bureau of Economic Research · USNew York University · US

Funding

Science/Technical CoreP2CHD041020 · NICHD · BROWN UNIVERSITY · PI Margot Jackson · 2016 to 2026
$7.6M
NICHD NIH HHS P2C HD041020
6 · The paper itself

Abstract

Folklore is the collection of traditional beliefs, customs, and stories of a community passed through the generations by word of mouth. We introduce to economics a unique catalog of oral traditions spanning approximately 1,000 societies. After validating the catalog's content by showing that the groups' motifs reflect known geographic and social attributes, we present two sets of applications. First, we illustrate how to fill in the gaps and expand upon a group's ethnographic record, focusing on political complexity, high gods, and trade. Second, we discuss how machine learning and human classification methods can help shed light on cultural traits, using gender roles, attitudes toward risk, and trust as examples. Societies with tales portraying men as dominant and women as submissive tend to relegate their women to subordinate positions in their communities, both historically and today. More risk-averse and less entrepreneurial people grew up listening to stories wherein competitions and challenges are more likely to be harmful than beneficial. Communities with low tolerance toward antisocial behavior, captured by the prevalence of tricksters being punished, are more trusting and prosperous today. These patterns hold across groups, countries, and second-generation immigrants. Overall, the results highlight the significance of folklore in cultural economics, calling for additional applications.

Identifiers

PMID34658674
PMCPMC8505355
OpenAlexW4210718747

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.