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...
Gespeichert in:
Veröffentlicht in: | Scientometrics 2024-04, Vol.129 (4), p.2455-2468 |
---|---|
1. Verfasser: | |
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 & Information Sciences Abstracts (LISA)</collection><collection>Library & 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 |