Jeff Pooley

@jpooley.bsky.social

A media scholar - jeffpooley.com/about

"The journal roughly doubled its publication volume from nearly 5,000 articles in 2023 to over 9,600 in 2024, and published over 10,300 articles in 2025." Good illustration of why commercial publishers are not passive victims of fraudulent behaviour but have actively created the conditions for it.

Retraction Watch@retractionwatch.com · 4w ago

Since June @elsevierconnect.bsky.social has retracted 120 papers from the journal. According to the retraction notices, the journal identified “[s]ystematic, coordinated, and widespread manipulation of the peer-review process.”

What's at stake in seeing self-optimization as a sacred pursuit? Focusing on a group I call "masculine optimization influencers," I dive into the grindset. Come for discussions of shame and disgust, and stay for a chat about cold plunges as a baptismal practice. www.tandfonline.com/eprint/Q5A2T...

Masculine optimization influencers and the sacrality of self-optimization

Self-optimization has become a dominant idiom of contemporary American masculinity, crystallizing in a rising cohort of male influencers centered around reaching ‘maximum potential’ physically and ...

tandfonline.com

So, the premise is because AI is further burdening peer-review, we should implement it across the publishing process. This uses inevitability rhetoric, and noticing a pattern of those who are developing AI tools, or building their career and status around AI expertise, saying we need to use more AI

The Scholarly Kitchen@scholarlykitchen.bsky.social · 2mo ago

Guest Post — Now is the Time for AI in Peer Review, and Publishing Policies Need to Recognize This scholarlykitchen.sspnet.org/2026/06/30/g...

"What Wittgenstein—and the many other Romantically inclined intellectuals who got a bad vibe from the twentieth century's thoughtless faith in scientific progress—didn't anticipate is that the threat of annihilation would one day become a selling point for technology" www.commonwealmagazine.org/wi..

Wittgenstein’s Apocalypse | Commonweal Magazine

Ludwig Wittgenstein believed the age of technology would be the beginning of the end for humanity. The increasing ubiquity of AI may prove him right.

commonwealmagazine.org

Jacques Berlinerblau, our campus jester: "… my prediction [is] that by 2035, drones will be professors. They'll whir and zigzag above the students' heads. The gizmos will dispense AI-generated mash-ups of a million compressed lectures in Kylie Jenner's voice." www.chronicle.com/article/the...

Opinion | The Coming Faculty Class War, and Other Prophecies

Surveillance, billionaires, and drone professors. A scholar looks ahead and doesn’t like what he sees.

chronicle.com

The Matthew effect means prominent and well-cited scholars tend to receive still more prominence and citations, whereas less-cited scholars tend to slip into further obscurity over time. How will this manifest in AI summary? @jpooley.bsky.social for @lseimpactblog.bsky.social

The Matthew effect in AI summary - LSE Impact

AI research tools are trained on a literature that is structured by an unequal distribution of attention. Does their use simply recreate these biases ?

blogs.lse.ac.uk

Good piece by Jefferson Pooley on how LLM-powered “research” tools like Google’s “Deep Research” and Elsevier’s “AI Discovery” likely strengthen the “Matthew effect”: highly-cited authors are amplified while undercited (often female) authors are increasingly ignored: blogs.lse.ac.uk/impactofsoci...

The Matthew effect in AI summary - LSE Impact

AI research tools are trained on a literature that is structured by an unequal distribution of attention. Does their use simply recreate these biases ?

blogs.lse.ac.uk

"If we hand off the work to computational probability and the profit motive, we may reproduce, or perhaps worsen, an academic “class structure” with all of its accumulated (and now hidden) injustices." Post from @jpooley.bsky.social on the "Matthew effect in AI summary"

The Matthew effect in AI summary - LSE Impact

AI research tools are trained on a literature that is structured by an unequal distribution of attention. Does their use simply recreate these biases ?

blogs.lse.ac.uk