Skewed distributions of scientists’ productivity: a research program for the empirical analysis

Only a few scientists are able to publish a substantial number of papers every year; most of the scientists have an output of only a few publications or no publications at all. Several theories (e.g., the “sacred spark” theory) have been proposed in the past to explain these productivity differences...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Scientometrics 2024-04, Vol.129 (4), p.2455-2468
1. Verfasser: Bornmann, Lutz
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 2468
container_issue 4
container_start_page 2455
container_title Scientometrics
container_volume 129
creator Bornmann, Lutz
description Only a few scientists are able to publish a substantial number of papers every year; most of the scientists have an output of only a few publications or no publications at all. Several theories (e.g., the “sacred spark” theory) have been proposed in the past to explain these productivity differences that are complementary and focus on different aspects in the publication process. This study is intended to introduce a research program for studying productivity differences in science (skewed distributions of scientists’ productivity). The program is based on the Anna Karenina Principle (AKP). The AKP states that success in research is the result of several prerequisites that are multiplicatively related. Great success results from prerequisites that must be all given. If at least one prerequisite is not given, failure follows, whereby the failure is specific to the set of given and missing prerequisites. High productivity is given for the few scientists who fulfill all prerequisites (e.g., high motivation, pronounced creativity, reputational professional position, early important papers in high-impact journals), and low productivity is connected to a specific combination of missing and fulfilled prerequisites for many scientists. Besides the AKP as theoretical principle, the program for studying productivity differences includes a mathematical concept explaining skewed distributions and statistical methods for empirical productivity analyses.
doi_str_mv 10.1007/s11192-024-04962-z
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3055503293</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3055503293</sourcerecordid><originalsourceid>FETCH-LOGICAL-c314t-91fba0677a5e88a6742bd73598cd5a52f3b2ea6310da2dd237c3306bb2de78f93</originalsourceid><addsrcrecordid>eNp9kMtOwzAQRS0EEqXwA6wssQ74EScOO1TxkiqxANaWYzutS5sUjwNqV_wGv8eX4BIkdqxGmrlndHUQOqXknBJSXgCltGIZYXlG8qpg2XYPjaiQMmOyoPtoRCiXWUU5OURHAAuSIE7kCOnHF_fuLLYeYvB1H33XAu4aDMa7NqYtfH184nXobG-if_Nxc4k1Dg6cDma-O8yCXuGmCzjOHXartQ_e6CXWrV5uwMMxOmj0EtzJ7xyj55vrp8ldNn24vZ9cTTPDaR5Tt6bWpChLLZyUuihzVtuSi0oaK7RgDa-Z0wWnxGpmLeOl4ZwUdc2sK2VT8TE6G_6mSq-9g6gWXR9SCVCcCCEIZxVPKTakTOgAgmvUOviVDhtFidqpVINKlVSqH5VqmyA-QJDC7cyFv9f_UN8bknoc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3055503293</pqid></control><display><type>article</type><title>Skewed distributions of scientists’ productivity: a research program for the empirical analysis</title><source>SpringerLink Journals</source><creator>Bornmann, Lutz</creator><creatorcontrib>Bornmann, Lutz</creatorcontrib><description>Only a few scientists are able to publish a substantial number of papers every year; most of the scientists have an output of only a few publications or no publications at all. Several theories (e.g., the “sacred spark” theory) have been proposed in the past to explain these productivity differences that are complementary and focus on different aspects in the publication process. This study is intended to introduce a research program for studying productivity differences in science (skewed distributions of scientists’ productivity). The program is based on the Anna Karenina Principle (AKP). The AKP states that success in research is the result of several prerequisites that are multiplicatively related. Great success results from prerequisites that must be all given. If at least one prerequisite is not given, failure follows, whereby the failure is specific to the set of given and missing prerequisites. High productivity is given for the few scientists who fulfill all prerequisites (e.g., high motivation, pronounced creativity, reputational professional position, early important papers in high-impact journals), and low productivity is connected to a specific combination of missing and fulfilled prerequisites for many scientists. Besides the AKP as theoretical principle, the program for studying productivity differences includes a mathematical concept explaining skewed distributions and statistical methods for empirical productivity analyses.</description><identifier>ISSN: 0138-9130</identifier><identifier>EISSN: 1588-2861</identifier><identifier>DOI: 10.1007/s11192-024-04962-z</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Computer Science ; Empirical analysis ; Information Storage and Retrieval ; Library Science ; Principles ; Productivity ; Scientists ; Skewed distributions ; Statistical methods</subject><ispartof>Scientometrics, 2024-04, Vol.129 (4), p.2455-2468</ispartof><rights>The Author(s) 2024</rights><rights>The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c314t-91fba0677a5e88a6742bd73598cd5a52f3b2ea6310da2dd237c3306bb2de78f93</cites><orcidid>0000-0003-0810-7091</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11192-024-04962-z$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11192-024-04962-z$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Bornmann, Lutz</creatorcontrib><title>Skewed distributions of scientists’ productivity: a research program for the empirical analysis</title><title>Scientometrics</title><addtitle>Scientometrics</addtitle><description>Only a few scientists are able to publish a substantial number of papers every year; most of the scientists have an output of only a few publications or no publications at all. Several theories (e.g., the “sacred spark” theory) have been proposed in the past to explain these productivity differences that are complementary and focus on different aspects in the publication process. This study is intended to introduce a research program for studying productivity differences in science (skewed distributions of scientists’ productivity). The program is based on the Anna Karenina Principle (AKP). The AKP states that success in research is the result of several prerequisites that are multiplicatively related. Great success results from prerequisites that must be all given. If at least one prerequisite is not given, failure follows, whereby the failure is specific to the set of given and missing prerequisites. High productivity is given for the few scientists who fulfill all prerequisites (e.g., high motivation, pronounced creativity, reputational professional position, early important papers in high-impact journals), and low productivity is connected to a specific combination of missing and fulfilled prerequisites for many scientists. Besides the AKP as theoretical principle, the program for studying productivity differences includes a mathematical concept explaining skewed distributions and statistical methods for empirical productivity analyses.</description><subject>Computer Science</subject><subject>Empirical analysis</subject><subject>Information Storage and Retrieval</subject><subject>Library Science</subject><subject>Principles</subject><subject>Productivity</subject><subject>Scientists</subject><subject>Skewed distributions</subject><subject>Statistical methods</subject><issn>0138-9130</issn><issn>1588-2861</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><recordid>eNp9kMtOwzAQRS0EEqXwA6wssQ74EScOO1TxkiqxANaWYzutS5sUjwNqV_wGv8eX4BIkdqxGmrlndHUQOqXknBJSXgCltGIZYXlG8qpg2XYPjaiQMmOyoPtoRCiXWUU5OURHAAuSIE7kCOnHF_fuLLYeYvB1H33XAu4aDMa7NqYtfH184nXobG-if_Nxc4k1Dg6cDma-O8yCXuGmCzjOHXartQ_e6CXWrV5uwMMxOmj0EtzJ7xyj55vrp8ldNn24vZ9cTTPDaR5Tt6bWpChLLZyUuihzVtuSi0oaK7RgDa-Z0wWnxGpmLeOl4ZwUdc2sK2VT8TE6G_6mSq-9g6gWXR9SCVCcCCEIZxVPKTakTOgAgmvUOviVDhtFidqpVINKlVSqH5VqmyA-QJDC7cyFv9f_UN8bknoc</recordid><startdate>20240401</startdate><enddate>20240401</enddate><creator>Bornmann, Lutz</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>E3H</scope><scope>F2A</scope><orcidid>https://orcid.org/0000-0003-0810-7091</orcidid></search><sort><creationdate>20240401</creationdate><title>Skewed distributions of scientists’ productivity: a research program for the empirical analysis</title><author>Bornmann, Lutz</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c314t-91fba0677a5e88a6742bd73598cd5a52f3b2ea6310da2dd237c3306bb2de78f93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Computer Science</topic><topic>Empirical analysis</topic><topic>Information Storage and Retrieval</topic><topic>Library Science</topic><topic>Principles</topic><topic>Productivity</topic><topic>Scientists</topic><topic>Skewed distributions</topic><topic>Statistical methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bornmann, Lutz</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><collection>Library &amp; Information Sciences Abstracts (LISA)</collection><collection>Library &amp; Information Science Abstracts (LISA)</collection><jtitle>Scientometrics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bornmann, Lutz</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Skewed distributions of scientists’ productivity: a research program for the empirical analysis</atitle><jtitle>Scientometrics</jtitle><stitle>Scientometrics</stitle><date>2024-04-01</date><risdate>2024</risdate><volume>129</volume><issue>4</issue><spage>2455</spage><epage>2468</epage><pages>2455-2468</pages><issn>0138-9130</issn><eissn>1588-2861</eissn><abstract>Only a few scientists are able to publish a substantial number of papers every year; most of the scientists have an output of only a few publications or no publications at all. Several theories (e.g., the “sacred spark” theory) have been proposed in the past to explain these productivity differences that are complementary and focus on different aspects in the publication process. This study is intended to introduce a research program for studying productivity differences in science (skewed distributions of scientists’ productivity). The program is based on the Anna Karenina Principle (AKP). The AKP states that success in research is the result of several prerequisites that are multiplicatively related. Great success results from prerequisites that must be all given. If at least one prerequisite is not given, failure follows, whereby the failure is specific to the set of given and missing prerequisites. High productivity is given for the few scientists who fulfill all prerequisites (e.g., high motivation, pronounced creativity, reputational professional position, early important papers in high-impact journals), and low productivity is connected to a specific combination of missing and fulfilled prerequisites for many scientists. Besides the AKP as theoretical principle, the program for studying productivity differences includes a mathematical concept explaining skewed distributions and statistical methods for empirical productivity analyses.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s11192-024-04962-z</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0003-0810-7091</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0138-9130
ispartof Scientometrics, 2024-04, Vol.129 (4), p.2455-2468
issn 0138-9130
1588-2861
language eng
recordid cdi_proquest_journals_3055503293
source SpringerLink Journals
subjects Computer Science
Empirical analysis
Information Storage and Retrieval
Library Science
Principles
Productivity
Scientists
Skewed distributions
Statistical methods
title Skewed distributions of scientists’ productivity: a research program for the empirical analysis
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T05%3A49%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Skewed%20distributions%20of%20scientists%E2%80%99%20productivity:%20a%20research%20program%20for%20the%20empirical%20analysis&rft.jtitle=Scientometrics&rft.au=Bornmann,%20Lutz&rft.date=2024-04-01&rft.volume=129&rft.issue=4&rft.spage=2455&rft.epage=2468&rft.pages=2455-2468&rft.issn=0138-9130&rft.eissn=1588-2861&rft_id=info:doi/10.1007/s11192-024-04962-z&rft_dat=%3Cproquest_cross%3E3055503293%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3055503293&rft_id=info:pmid/&rfr_iscdi=true