Evidence map›Paper›PMID 37233333›Full record

ArticleJournal of Intelligence2023

Lay Definitions of Intelligence, Knowledge, and Memory: Inter- and Independence of Constructs.

Jennifer H Coane, John Cipollini, Talia E Barrett, Joshua Kavaler, Sharda Umanath

Open access · goldAbstract read
In one paragraph

Article in Journal of Intelligence, 2023. 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
1.1field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

5 authors at 2 institutions in 1 country.

Jennifer H CoaneDepartment of Psychology, Colby College, Waterville, ME 04901, USA.ORCID 0000-0002-0934-0250
John CipolliniDepartment of Psychology, Colby College, Waterville, ME 04901, USA.
Talia E BarrettDepartment of Psychology, Colby College, Waterville, ME 04901, USA.
Joshua KavalerDepartment of Psychology, Colby College, Waterville, ME 04901, USA.ORCID 0000-0002-4603-5781
Sharda UmanathDepartment of Psychological Science, Claremont McKenna College, Claremont, CA 91711, USA.ORCID 0000-0002-6699-4357
Colby College · USClaremont McKenna College · US

Funding

James S. McDonnell Foundation 220020426
6 · The paper itself

Abstract

The present study examined how lay participants define the following concepts used widely in psychology: being intelligent, knowing, and remembering. In the scientific community, knowledge overlaps with the contents of semantic memory, crystallized intelligence reflects the accumulation of knowledge, knowledge and event memory interact, and fluid intelligence and working memory correlate. Naturally, the lay public has implicit theories of these constructs. These theories mainly distinguish between intelligent and unintelligent behaviors and tend to include characteristics outside psychometric studies of intelligence, such as emotional intelligence. Here, we asked lay participants from the online platform Prolific to explain "what does being intelligent mean to you?" as well as "knowing" and "remembering" to understand their degree of alignment with theoretical conceptualizations in the research community. Qualitative coding of participant definitions showed that intelligence and knowledge are closely related, but asymmetrically-when defining what it means to be intelligent, participants reference knowledge, but intelligence is not considered in explaining

Indexed as

face validityintelligenceknowledgememorymetacognition

Identifiers

PMID37233333
PMCPMC10218958
OpenAlexW4367310090

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.