Evidence map›Paper›PMID 35363795›Full record

ArticlePloS one2022

Multiple correspondence analysis as a tool for examining Nobel Prize data from 1901 to 2018.

T Alhuzali, E J Beh, E Stojanovski

Abstract readHistorical Article
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

3 authors.

T AlhuzaliSchool of Information & Physical Sciences, College of Engineering, Science and Environment, University of Newcastle, Callaghan NSW, Australia.ORCID 0000-0002-0406-4859
E J BehSchool of Information & Physical Sciences, College of Engineering, Science and Environment, University of Newcastle, Callaghan NSW, Australia.
E StojanovskiSchool of Information & Physical Sciences, College of Engineering, Science and Environment, University of Newcastle, Callaghan NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The main goal of this paper is to examine Nobel Prize data by studying the association among the laureate's country of birth or residence, discipline, time period in which the Nobel Prize was awarded, and gender of the recipient. Multiple correspondence analysis is used as a tool to examine the association between these four categorical variables by cross classifying them in the form of a four-way contingency table. The data that we examine comprise Nobel Prize recipients from 1901 to 2018 (inclusive) from eight-developed countries, with a total sample of 785 Nobel Prize recipients. The countries include Canada, France, Germany, Italy, Japan, Russia, the British Isles, and the USA and the disciplines in which the individuals were awarded the prizes include chemistry, physics, physiology or medicine, literature, economics, and peace.

Indexed as

Awards and PrizesMedicineGermanyHistory, 20th CenturyHumansNobel PrizePhysics

Identifiers

PMID35363795
PMCPMC8974957

What OpenQuestion holds

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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.