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We can all recognise the ambitious researcher at the conference who is anxious to advertise their own work while affecting interest in the keynote speaker’s presentation. It resonates with my current work on academic self-promotion via university profile pages. And I start to wonder, is a new academic habitus is beginning to emerge?
Shannon had a weakness for juggling and unicycles, but his fingerprints are on every electronic device we own.
Johannes Haushofer bravely posts document listing degree programs he did not get in to and academic positions he did not get
Billionaires are funding lots of grandiose plans. Welcome their ambition
A new analysis finds that 3.8 percent of scientific studies have images duplicated from another paper.
Science magazine just published a great piece on the utility of Sci-Hub. Unfortunately, its defense of its own business model is flawed.
Carlo Doglioni aims to concentrate on science, leaving trial and corruption allegations behind
13 tips to make submitting your paper a breeze
In 2012, network scientist and data theorist Samuel Arbesman published a disturbing thesis: What we think of as established knowledge decays over time.
Concerns over AI are not simply fear-mongering. Progress in the field will affect society profoundly, and it is important to make sure that the changes benefit everyone.
A discussion of the common underpinning problems with the scientific and data analytic practices and point to tools and behaviors that can be implemented to reduce the problems with published scientific results.
An exclusive look at data from the controversial web site Sci-Hub reveals that the whole world, both poor and rich, is reading pirated research papers.
A new open science business model charges those who want to keep information private to subsidise those who share it
In this interview with EuroScientist, Lawrence Rajendran explains why he created Matters, to change the way we communicate science.
For every characteristic of uberisation, there is a parallel in the world of research. This raises the question of whether research was "uberised" before Uber even existed?
If academic discoveries turn out to be wrong, one drug company wants its money back.
The impact factor is academia’s worst nightmare. So much has been written about its flaws, both in calculation and application, that there is little point in reiterating the same tired points here …
Turning scientific evidence into policy exposes a gulf between how scientists think and how policymakers work. Here’s what scientists need to know
Empowering the Next Generation to Advance Open Access, Open Education and Open Data.
David Kent breaks down an eLife article that suggests peer review scores cannot distinguish very good grants from excellent grants. In fact, at a certain point in the process, it is pretty much a random lottery.
