at this point no one cares, but i was invited to talk about the high-rep retraction saga, and once again, i find myself perplexed at the exclusion of confirmatory results in any calculation in a study making a key claim about the inclusion of confirmatory studies making results highly replicable.
Dec 15, 2025 at 9:51 PM
Retraction Note: High replicability of newly discovered social-behavioural findings is achievable
Nature Human Behaviour - Retraction Note: High replicability of newly discovered social-behavioural findings is achievable
Papers and peer reviews with evidence of ChatGPT writing
Retraction Watch readers have likely heard about papers showing evidence that they were written by ChatGPT, including one that went viral. We and others have reported on the phenomenon. Here’…
Andreas De Block on Twitter / X
It took Nature three years to publish this rebuttal, which clearly demonstrates the fundamental flaws in the original paper. In the meantime, the paper's conclusions influenced scientific debate and policy decisions. Such delays in correcting flawed research do real damage. https://t.co/QI3Ei3PE70— Andreas De Block (@DeblockBlock) August 13, 2026
The State of Papers, Retractions, and Preprints: Evidence from the CrossRef Database (2004-2024)
A 20-year analysis of CrossRef metadata demonstrates that global scholarly output -- encompassing publications, retractions, and preprints -- exhibits strikingly inertial growth, well-described by exponential, quadratic, and logistic models with nearly indistinguishable goodness-of-fit. Retraction dynamics, in particular, remain stable and minimally affected by the COVID-19 shock, which contributed less than 1% to total notices. Since 2004, publications doubled every 9.8 years, retractions every 11.4 years, and preprints at the fastest rate, every 5.6 years. The findings underscore a system primed for ongoing stress at unchanged structural bottlenecks. Although model forecasts diverge beyond 2024, the evidence suggests that the future trajectory of scholarly communication will be determined by persistent systemic inertia rather than episodic disruptions -- unless intentionally redirected by policy or AI-driven reform.
More than 10,000 research papers were retracted in 2023 — a new record
The number of articles being retracted rose sharply this year. Integrity experts say that this is only the tip of the iceberg.
More than 10,000 research papers were retracted in 2023 — a new record
The number of articles being retracted rose sharply this year. Integrity experts say that this is only the tip of the iceberg.
When Nature Calls: The Enshittification of Science and Its Enablers
Proof-of-work papers, policy laundering, and the collapse of self-correction
How Ten Publishers Retract Research
Retractions are the primary mechanism for correcting the scholarly record, yet publishers differ markedly in how they use them. We present a bibliometric analysis of 46,087 retractions across 10 major publishers using data from the Retraction Watch database (1997-2026), examining retraction rates, reasons, temporal trends, and geographic distributions, among other dimensions. Normalized retraction rates vary by two orders of magnitude, from Elsevier's 3.97 per 10,000 publications to Hindawi's 320.02. China-affiliated authors account for the largest share of retractions at every publisher. Retraction lags and reason profiles also vary widely across publishers. Among the ten publishers, ACM is an outlier in its retraction profile. ACM's normalized rate is mid-range (5.65), yet 98.3% of its 354 retractions are related to one incident. Seven of the ten most common global retraction reasons (including misconduct, plagiarism, and data concerns) are entirely absent from ACM's record. ACM's first retraction dates to 2020, despite a catalog dating to 1997. ACM self-describes its retraction threshold as "extremely high." We discuss this threshold in relation to the COPE retraction guidelines and the implications of ACM's non-public dark archive of removed works.
The associations of social media attention, visibility, disinformation and retraction initiators with time to retraction: a Cox regression analysis
Purpose This study examines how retraction reasons, retraction initiators, journal visibility, access models and Twitter activity associate with the speed of retracting flawed scientific publications. Design/methodology/approach Using a Cox proportional hazards model, we analyzed 1,179 articles retracted in 2019–2021, including a subset of 98 papers tweeted before retraction. Findings The results reveal that higher journal impact factor and open-access status were associated with faster retractions. However, a significant negative interaction indicated that the effect of high-impact journals diminished for open-access publications. Journal-initiated retractions were slower overall, except in cases of misconduct such as co-authorship deception and plagiarism, where journals acted more quickly. Among retraction reasons, only deception in co-authoring was associated with significantly slower retractions, but this trend reversed when journals led the process. The association of social media attention with retraction speed was statistically robust, albeit modest in magnitude: each additional pre-retraction tweet was associated with a slight reduction in time to retraction. Bootstrap validation confirmed the stability of this finding. Originality/value Public scrutiny, institutional responsibility and publication visibility jointly shape the time to retraction. This study advances altmetrics discourse by positioning social media as a conditional, yet meaningful, participant in the retraction lifecycle. Beyond altmetrics, our findings highlight retractions as part of a broader network of relationships between public accountability, digital ethics and science communication, positioning them as moments of accountability shaped jointly by journals, ethical responsibilities and digital publics.
An article about data visualization was retracted 1.5 years after I pointed out errors. The notice says that "concerns were raised". I spend dozens of hours contacting authors and editors, reproducing analyses, and following up on ignored emails. But I'm not mentioned in the retraction notice.
RETRACTED: A Perception Study for Unit Charts in the Context of Large-Magnitude Data Representation
www.mdpi.comHow times change! A decade ago, a failed replication of work by the same lab led to 'repligate' and blog posts such as psychol.cam.ac.uk/cece/blog Now, failed replications can be published an no one blinks an eye. That is progress due to all the scholars working hard to improve science!
I'll just comment on my impressions of their conclusions in a thread here. Worth sharing how I see it unfolding internally. (I signed up for their email spam to read this so yes, I am a hero.)
Sue Smith
"The AI engineering impact data shows that output is up. It also shows that the work required to ensure that output is safe, correct, and maintainable has not decreased. It has increased substantially." Aye, if only any of us had been saying this from day one 🤡 faros.ai/blog/ai-acceleration-whiplash…
I'll just comment on my impressions of their conclusions in a thread here. Worth sharing how I see it unfolding internally. (I signed up for their email spam to read this so yes, I am a hero.)
Sue Smith
"The AI engineering impact data shows that output is up. It also shows that the work required to ensure that output is safe, correct, and maintainable has not decreased. It has increased substantially." Aye, if only any of us had been saying this from day one 🤡 faros.ai/blog/ai-acceleration-whiplash…
In our new paper of how Bluesky users discuss retracted papers, we found: ✅ 90% of Bluesky posts show "good practices" (flagging issues/retraction status) ❌ Only 10% show "bad practices" This highlights Bluesky's vital role in responsible science communication! arxiv.org/abs/2605.04334
