Manuscript Rejection Based Solely on Divergent Perspectives: A Critique of Reviewer Consensus as Grounds for Academic Dismissal
Unrefuted Arguments Retain Scholarly Value and Merit Consideration for Publication
Response to Technology in Society Rejection (TECHIS-D-25-05905)
Commentary on Academic Journal Rejection Letters: A Pattern of Systemic Bias
Preprint:
Yue Liu, Why Are Research Findings Supported by Experimental Data with High Probability Often False? --Critical Analysis of the Replication Crisis and Statistical Bias in Scientific Literature, Preprints.org, preprint, 2025, 10.20944/preprints202507.1953.v1
Comments and responses
Yue Liu
College of Chemistry and Chemical Engineering, Shenyang Normal University, Shenyang, P. R. China,110034
yueliusd@163.com
ORCID: https://orcid.org/0000-0001-5924-9730
1. Comments
2025年08月10日 19:32 (星期日)
Ms. Ref. No.: JOBR-D-25-06373
Title: Why Are Research Findings Supported by Experimental Data with High Probability Often False?
Journal of Business Research
Dear Prof. Yue Liu,
Thank you for submitting your manuscript to the Journal of Business Research. We have read your paper with respect to its potential suitability for JBR. After considering the manuscript, I have decided to reject your paper and consequently it will not be sent out for review.
Journal of Business Research is a scholarly journal that publishes the highest level of research. To be published in JBR, a manuscript must fit the scope of the journal, significantly advance theory, provide managerially-meaningful and generalizable empirical research.
Additional comments (if any):
The research results reported are too premature for publication. More work is needed to substantiate the conclusions in your manuscript.
Your assertion that "research findings that appear to be strongly supported by experimental data with high statistical probability are often false" is not correct. Your reference to "John Ioannidis's seminal 2005 assertion that "most published research findings are false" is very outdated.
Yours sincerely,
Junhong Chu
Senior Editor
Journal of Business Research
2 Responses
2025年08月10日 22:54 (星期日)
https://blog.sciencenet.cn/blog-3589443-1497148.html
预印本：为什么低质量文章比颠覆性创新成果更容易发表
Dear Dr. Chu,
Thank you for your response regarding manuscript JOBR-D-25-06373. While I respectfully accept the editorial decision, I believe there are fundamental characterizations in your assessment that merit clarification, particularly regarding the scientific validity and current relevance of the work presented.
Regarding the "Outdated" Nature of Ioannidis (2005)
Your characterization of Ioannidis's 2005 work as "very outdated" contradicts substantial contemporary evidence. Recent research continues to validate and extend his fundamental insights:
Current Replication Crisis Data (2024-2025): The 2025 Presidential Commission to Make America Healthy Again explicitly identifies the "replication crisis" as a priority concern, with NIH Director Jay Bhattacharya acknowledging that "many research findings are not reproducible" due to "systemic issues" rather than individual failings.
Contemporary Validation: A 2024 meta-analysis by Patil, Peng, and Leek found that while 77% of replication studies fall within statistical prediction intervals, this actually supports rather than refutes Ioannidis's core mathematical framework about positive predictive values in research findings.
Ongoing Relevance: The disruption index literature (Nature, 2023; MIT Press, 2024) demonstrates that scientific papers are becoming less disruptive over time, consistent with our manuscript's argument about the suppression of innovative findings through current publication practices.
Regarding Theoretical Advancement in Business Research
Your comment about insufficient theoretical advancement appears to misunderstand our contribution. Our manuscript directly addresses JBR's stated mission to publish research that "significantly advance[s] theory" by proposing a novel theoretical framework connecting:
Economic principles of laissez-faire governance to scientific innovation
Mathematical models of low-probability events to breakthrough discoveries
Institutional theory regarding peer review bias and minority viewpoint suppression
This interdisciplinary approach aligns with current calls in management journals for "theory elaboration" that challenges existing paradigms (Fisher & Aguinis, 2017; Academy of Management Journal, 2024).
Evidence for "Premature" Assessment
The assertion that our findings are "too premature" conflicts with substantial empirical evidence presented in our manuscript:
Quantified Publication Bias: Recent data shows paper mills and fraudulent studies are contaminating scientific literature at unprecedented rates, with major publishers closing entire journals due to systematic manipulation.
Documented Suppression of Innovation: The 2024 PNAS special issue on academic publishing explicitly acknowledges how current incentive structures "pressure scholars to maximize publication metrics" rather than pursue genuine innovation.
Historical Precedent: Our analysis demonstrates that transformative discoveries (Newton, Einstein, Watson & Crick) emerged without modern peer review constraints that now systematically reject minority viewpoints.
Response to Methodological Concerns
Your critique appears to conflate our theoretical framework with empirical inadequacy. However, our manuscript employs established methodological approaches consistent with business research standards:
Mathematical modeling of institutional incentive structures
Historical case study analysis of scientific breakthroughs
Comparative institutional analysis (planned vs. market economies)
Theory elaboration methodology for challenging existing paradigms
The Irony of Rejection
Most significantly, this rejection itself exemplifies the core thesis of our manuscript. As documented in our research, peer reviewers systematically exhibit "confirmation bias toward findings that support established theories" while discriminating against research that challenges mainstream paradigms. Your dismissal of well-documented replication crisis evidence as "outdated" and characterization of extensive theoretical development as "premature" precisely demonstrates the institutional bias we analyze.
The accompanying blog post you reference (https://blog.sciencenet.cn/blog-3589443-1497148.html) supports our central argument that low-quality articles receive preferential treatment over disruptive innovations in current publication systems.
Constructive Path Forward
Given JBR's commitment to "rigorous, relevant, and potentially impactful" research, I respectfully suggest that dismissing extensively documented phenomena as "incorrect" or "outdated" without engaging with current evidence may not serve the journal's scholarly mission. Our manuscript addresses fundamental questions about how institutional structures either enable or suppress scientific innovation—precisely the type of theory-driven research that advances business scholarship.
…
Thank you for your consideration.
Sincerely,
Prof. Yue Liu
1. Liu, Yue, The Paradox of Academic Publishing: Why Low-Quality Research Thrives While Disruptive Innovation Struggles, Qeios, Preprint, 2025, https://doi.org/10.32388/QD8GGF
2. Liu, Yue, Why Has Physics Come to a Standstill? The Case of Microwave Absorption Theory and the State of Scientific Progress, 2025, PsyArXiv Preprints, https://doi.org/10.31234/osf.io/5v8s6_v1
3. Liu, Yue, Theoretical Primacy in Scientific Inquiry: A Critique of the Empirical Orthodoxy in Modern Research (August 05, 2025). Available at SSRN: https://ssrn.com/abstract=5379953 or http://dx.doi.org/10.2139/ssrn.5379953
4. Liu, Yue, The Misapplication of Statistical Methods in Liberal Arts: A Critical Analysis of Academic Publishing Bias Against Theoretical Research (August 01, 2025). Available at SSRN: https://ssrn.com/abstract=5376778 or http://dx.doi.org/10.2139/ssrn.5376778
5. Yue Liu, The Reluctance to Criticize the Errors of the Majority: Authority, Conformity, and Academic Silence in Scholarly Discourse, Preprints.org, preprint, 2025, DOI:10.20944/preprints202507.2515.v1
6. Yue Liu, The Entrenched Problems of Scientific Progress: An Analysis of Institutional Resistance and Systemic Barriers to Innovation, Preprints.org, preprint, 2025, DOI:10.20944/preprints202507.2152.v1
7. Yue Liu, Why Are Research Findings Supported by Experimental Data with High Probability Often False? --Critical Analysis of the Replication Crisis and Statistical Bias in Scientific Literature, Preprints.org, preprint, 2025, 10.20944/preprints202507.1953.v1
8. Yue Liu, Scientific Accountability: The Case for Personal Responsibility in Academic Error Correction, Qeios, Preprint, 2025, https://doi.org/10.32388/M4GGKZ
9. Yue Liu. Non-Mainstream Scientific Viewpoints in Microwave Absorption Research: Peer Review, Academic Integrity, and Cargo Cult Science, Preprints.org, preprint, 2025, DOI:10.20944/preprints202507.0015.v2, Supplementary Materials
10. Yue Liu, Revolutionary Wave Mechanics Theory Challenges Scientific Establishment (July 07, 2025). Available at SSRN: https://ssrn.com/abstract=5349919 or http://dx.doi.org/10.2139/ssrn.5349919
11. Yue Liu, Michael G.B. Drew, Ying Liu,Theoretical Insights Manifested by Wave Mechanics Theory of Microwave Absorption—Part 1: A Theoretical Perspective, Preprints.org, Preprint, 2025, DOI:10.20944/preprints202503.0314.v4, supplementary.docx (919.54KB ).
12. Yue Liu, Michael G.B. Drew, Ying Liu, Theoretical Insights Manifested by Wave Mechanics Theory of Microwave Absorption—Part 2: A Perspective Based on the Responses from DeepSeek, Preprints.org, Preprint, 2025, DOI:10.20944/preprints202504.0447.v3, Supplementary Materials IVB. Liu Y, Drew MGB, Liu Y. Theoretical Insights Manifested by Wave Mechanics Theory of Microwave Absorption - A Perspective Based on the Responses from DeepSeek. Int J Phys Res Appl. 2025; 8(6): 149-155. Available from: https://dx.doi.org/10.29328/journal.ijpra.1001123, Supplementary Materials, DOI: 10.29328/journal.ijpra.1001123
Challenging the Desk-Rejection Dogma - yueliusd’s Substack
References
Why Most Published Research Findings Are False
https://en.wikipedia.org/wiki/Why_Most_Published_Research_Findings_Are_False
Amid White House claims of a research ‘replication crisis,’ scientists offer solutions
Actionable guidelines to improve ‘theory-related’ contributions to international business research
https://link.springer.com/article/10.1057/s41267-022-00567-x
Santangelo, G.D., Verbeke, A. Actionable guidelines to improve ‘theory-related’ contributions to international business research. J Int Bus Stud 53, 1843–1855 (2022). https://doi.org/10.1057/s41267-022-00567-x
3 The Novel Contribution and Practical Significance of This Research
This paper advances a critical but overlooked distinction in scientific methodology: while statistical approaches focus primarily on high-probability events, the most transformative scientific discoveries emerge from low-probability phenomena that are systematically neglected by current academic structures. Our core innovation lies not merely in demonstrating that high-probability events can be false—as established by Ioannidis—but more importantly, in revealing how low-probability events of genuine scientific importance are marginalized by probability-centric evaluation systems. Consider that the emergence of plant and animal life in nature represents quintessential low-probability events, yet these "statistical outliers" fundamentally shaped our biosphere. Similarly, the human body's remarkable self-healing mechanisms operate through low-probability biological processes that, despite extensive high-probability experimental approaches, remain impossible to replicate artificially in laboratories. Market economies succeed precisely because they create conditions enabling low-probability innovations to flourish through spontaneous order rather than centralized planning. This framework addresses urgent problems in contemporary academia: graduate students who should primarily focus on rigorous coursework to elevate their theoretical foundations are instead pressured into laboratories pursuing "innovation," resulting in the paradoxical phenomenon where "teaching standards continuously decline while SCI publication prestige continuously rises." Statistical methods incorrectly suggest that innovation is commonplace—that every master's and doctoral student can produce multiple high-impact publications, and even undergraduates routinely publish in SCI journals. This generates the false conclusion that "innovation is easy and achievable by everyone," when authentic innovation remains a rare, serendipitous event. Realistically, perhaps 5% of published SCI papers contain genuine innovation, despite universal claims of novelty, yet statistical methodologies cannot distinguish authentic breakthroughs from incremental modifications. The fundamental issue is that statistical methods' prerequisite assumptions—particularly the ability to identify true innovation—simply do not exist in practice, creating a measurement problem that undermines the entire evaluation system and perpetuates the very biases our research exposes.
Information：
科学网—预印本：为什么低质量文章比颠覆性创新成果更容易发表 - 刘跃的博文
https://blog.sciencenet.cn/blog-3589443-1497148.html
https://blog.sciencenet.cn/home.php?mod=space&uid=41701&do=blog&id=1496139#comment_5560929
大学生就是学习知识的，能做出有创新的论文是凤毛麟角。但是很多本科学生都能发表国际SCI论文，怀疑这些论文的创新是真的还是假的。
普遍认为硕士博士是搞研究的，发表论文理所应当。但是那么多硕士博士，每个人毕业都要有几篇SCI论文，怀疑这些大量的SCI论文中垃圾和造假的论文的比列有多少。
这些问题没有人问、没有人敢问、更没有人去认真研究。
现在硕士博士就是进实验室做实验搞“创新”。实际上创新可遇不可求，能做出真创新的能有5%就很了不起了。
现在硕士博士的课程是为了达到要求而设的，基本没有实质性的重视。
严格科学的教育体制应该是硕士和博士的理论水平必须上一个台阶，创新是锦上添花的事，可以没有。
实际情况恰恰相反，硕士博士提升了理论水平的凤毛麟角，SCI创新论文每个人都有几篇
https://blog.sciencenet.cn/home.php?mod=space&uid=41701&do=blog&id=1496139#comment_5560965
现代科学界问题很大。这不是哪一个国家的问题，是整个国际学术界的问题。
但是这个问题太大，打击面太大，没有人敢碰，
https://www.preprints.org/manuscript/202507.2515/v1
Yue Liu, The Reluctance to Criticize the Errors of the Majority: Authority, Conformity, and Academic Silence in Scholarly Discourse, Preprints.org, preprint, 2025, DOI:10.20944/preprints202507.2515.v1
垃圾文章和造假文章越来越多，因此获得利益的人越来越多，所以问题似滚雪球一样，越来越严重。
学术圈某种意义上像是个派系林立的“江湖”，学术权威如同“教主”一样，普通学者没有力量反抗其观点。
随着发表的错误论文越来越多，跟风研究的越来越多，大家都成了既得利益者，就默许了这些错误的观点继续流传下去。
———— 科技日报，2018-10-18 第01版：
今日要闻，骗了全世界十余年 干细胞“学术大牛”走下神坛
https://baijiahao.baidu.com/s?id=1614619477235832974&wfr=spider&for=pc
https://baijiahao.baidu.com/s?id=1614619476870888302
https://www.rmzxb.com.cn/c/2018-10-18/2193148.shtml
Liu, Yue, The Paradox of Academic Publishing: Why Low-Quality Research Thrives While Disruptive Innovation Struggles, Qeios, Preprint, 2025, https://doi.org/10.32388/QD8GGF
Liu, Yue, The Misapplication of Statistical Methods in Liberal Arts: A Critical Analysis of Academic Publishing Bias Against Theoretical Research (August 01, 2025). Available at SSRN: https://ssrn.com/abstract=5376778 or http://dx.doi.org/10.2139/ssrn.5376778
Business Research Relevance
Your assessment overlooks the direct relevance of our research to core business research areas defined in JBR's scope:
1. Innovation Management: Our analysis directly addresses how institutional structures enable or suppress business innovation—a central concern for entrepreneurship and strategic management research.
2. Organizational Behavior: The manuscript examines decision-making biases in academic organizations that parallel well-documented biases in business contexts.
3. Strategic Management: We provide insights into how organizations can structure environments to foster breakthrough innovations rather than incremental improvements.
4. Business Ethics: Our research addresses fundamental ethical issues in knowledge production that extend beyond academia to R&D management in business contexts.
Practical Implications for Business
The manuscript offers actionable insights for business leaders:
How to create organizational cultures that encourage low-probability, high-impact innovations
Why statistical approaches to evaluating innovation may systematically exclude transformative ideas
How deregulated, laissez-faire approaches can foster breakthrough discoveries in corporate R&D settings
These insights directly support JBR's mission to provide "meaningful debates in academia and practice" and generate research that "makes a difference to conceptual thinking and/or practice."
Theory Advancement
Contrary to your assessment, our manuscript advances theory in multiple ways:
Integrates economic principles (laissez-faire governance) with innovation theory
Develops mathematical models linking probability distributions to breakthrough discovery rates
Extends institutional theory to explain systematic biases in knowledge evaluation systems
This interdisciplinary theoretical contribution aligns with JBR's emphasis on examining "intricate relationships between many areas of business activity."
I respectfully maintain that dismissing this work without peer review represents precisely the kind of institutional bias our research identifies and seeks to address.