Evidence map›Paper›PMID 36645219›Full record

ArticleQuarterly journal of experimental psychology (2006)2023

Social and non-social categorisation in investment decisions and learning.

Maïka Telga, José A Alcalá, Juan Lupiáñez

Open access · hybridAbstract read
In one paragraph

Article in Quarterly journal of experimental psychology (2006), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 3 institutions in 2 countries.

Maïka TelgaDepartment of Experimental Psychology, University of Granada, Granada, Spain.ORCID 0000-0002-6792-0093
José A AlcaláUniversity of Jaén, Jaén, Spain.ORCID 0000-0002-0092-1462
Juan LupiáñezDepartment of Experimental Psychology, University of Granada, Granada, Spain.ORCID 0000-0001-6157-9894
Universidad Complutense de Madrid · ESUniversidad de Granada · ESUniversity of St Andrews · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Categorical processes allow us to make sense of the environment effortlessly by grouping stimuli sharing relevant features. Although these processes occur in both social and non-social contexts, motivational, affective, and epistemic factors specific to the social world may motivate individuation over categorisation of social compared with non-social stimuli. In one experiment, we tested this hypothesis by analysing the reliance on categorical versus individuating information when making investment decisions about social and non-social targets. In an adaptation of the iterative trust game, participants from three experimental groups had to predict the economic outcomes associated with either humans (i.e., social stimuli), artificial races (i.e., social-like stimuli), or artworks (i.e., non-social stimuli) to earn economic rewards. We observed that investment decisions with humans were initially biased by categorical information in the form of gender stereotypes, but later improved through an individuating learning approach. In contrast, decisions made with non-social stimuli were initially unbiased by categorical information, but the category-outcomes associations learned through repeated interactions were quickly used to categorise new targets. These results are discussed along with motivational and perceptual mechanisms involved in investment decisions and learning about social and non-social agents.

Indexed as

LearningTrustHumanscategorisationeconomic rewardindividuationlearningTrust game

Identifiers

PMID36645219
PMCPMC10655696
OpenAlexW4316687598

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.