2016
DOI: 10.1080/1046669x.2016.1186469
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Research Fraud and the Publish or Perish World of Academia

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Cited by 27 publications
(19 citation statements)
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“…12 In addition, as publish or perish lies at the root of academic advancement, the pressure to publish can "harm the quality of life of researchers, decreasing their satisfaction and undermining creativity." 13 It can be concluded that this indicator conflicts with SDG 4.…”
Section: Why Are Global University Ranking Indicators Incompatible Wimentioning
confidence: 96%
“…12 In addition, as publish or perish lies at the root of academic advancement, the pressure to publish can "harm the quality of life of researchers, decreasing their satisfaction and undermining creativity." 13 It can be concluded that this indicator conflicts with SDG 4.…”
Section: Why Are Global University Ranking Indicators Incompatible Wimentioning
confidence: 96%
“…This is related to the growing concentration of commercial publishing houses, which enhances their ability to exploit both the 'publish or perish' imperative of career-oriented scholars (and their current or future university employers) and the need of scientists to access the latest scientific output (Broad 1981; Association of Research Libraries 1998; Bauerlein et al 2010;Herndon 2016). The profitability of journal publishing and the need for authors to publish something somewhere have contributed to an increase in journal numbers, salami-sliced research reports, poor science and unethical editorial practices intended to boost profits (on predatory publishing, see Beall 2015).…”
Section: Experiments 2: Rethinking Entrepreneurial Universitiesmentioning
confidence: 99%
“…Data fabrication refers to actually creating fake data sets and results and presenting them as true findings. Related to this is data falsification, altering data to get publishable results, both of which undermine the integrity of the entire review and publication process [11]. "Pruning and massaging" can be undertaken through the use of inappropriate methods of data analysis, the (tacit) exclusion of outliers in data analysis [12].…”
Section: Research Misconductmentioning
confidence: 99%