Jonathan Eisen's suggestions for having diverse speakers at meetings→

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  1. Do not try to invite only the famous people or the people doing the "top" work. This usually biases one towards more established researchers (as in, older) and this alas also usually is accompanied by distortion of diversity.

  2. DO try to invite people across the breadth of career stages. Meetings to me should not be only about getting the PIs whose labs are doing the best work to talk. It should also be about giving opportunities to junior researchers - PhD students, post docs and junior faculty who are doing exciting work - perhaps more focused or smaller scale - but nevertheless exciting. If one opens up a invited speaker list to people at diverse career stages one generally greatly increases the gender and ethnic diversity.

10 simple rules to achieve conference speaker gender balance→

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Rule 2: Develop a Speaker Policy

A speaker policy captures what the committee is trying to achieve for its members and audience when putting together the speaker program. It can also help the committee measure outcome. A policy may state, for example, that the conference committee wants to achieve a gender balance of speakers that roughly reflects that of its audience. Depending on the conference or meeting, the policy might include scientific diversity, geographical distribution, ethnicity, and level of seniority in the speaker policy.

I don't see a lot of speaker policies for conferences I attend or know about - either they don't exist, or aren't advertised.

Calling attention to poor speaker gender ratio - even when it hurts→

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Great example of how to be proactive about equality from Jonathan Eisen.

If this was a symposium outside UC Davis the first thing I would do would be to post about it. To Twitter or my blog or both. And to critique them. Why? Because there is a bad history in STEM fields of having meetings and conferences have under-representation of women as speakers. And this has become a passion of mine and I write about it a lot. But I hesitated. Why? Because this was from UC Davis and many of the people involved are friends / colleagues. I did not want to anger them, or embarrass them. And I don't think there is any intentional bias here by any means. But, if I am going to critique people outside UC Davis, it seems like I should also apply the same standards to people inside UC Davis and to colleagues and friends.

Introduction to open science and data management→

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Great overview of some concrete ways to practice open science.

8. Let everyone watch.

Consider going open. That is, do all of your science out in the public eye, so that others can see what you’re up to. One way to do this is by keeping an open notebook. This concept throws out the idea that you should be a hoarder, not telling others of your results until the Big Reveal in the form of a publication. Instead, you keep your lab notebook (you do have one, right?) out in a public place, for anyone to peruse. Most often an open notebook takes the form of a blog or a wiki, and the researcher updates their notebook daily, weekly, or whatever is most appropriate. There are links to data, code, relevant publications, or other content that helps readers, and the researcher themselves, understand the research workflow.

Making your lab a "highly reliable organization"→

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Must-read from Jeff Rouder on applying characteristics of "highly reliable organizations" in a lab setting.

[M]istakes and other adverse events not only cost us time, they affect the trust other people may place in our data and analyses. We need to keep them at a minimum and understand them when they occur. So I began adapting the characteristics of highly reliable organizations for my lab. Making changes does take time and effort, but I suspect the rewards are well worth it.

We're talking about this in lab meeting this week, and starting to implement some of these ideas immediately.

The sad state of parental leave in the United States→

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Appalling.

And on the list of countries that mandate zero paternity leave is the United States. At least the U.S. is an equal opportunity denier. There is also no legally required maternity leave. For both parents, leave is up to the employer.

When leave is granted, the family benefits. Jody Heymann, dean of the UCLA Fielding School of Public Health, points to research from the Organization for Economic Co-operation and Development (OECD) showing that fathers who take leave after a child is born — especially those who take at least two weeks off — are more likely to be involved in childcare in the first years of life. OECD research also found that children with highly involved fathers perform better on cognitive tests.

Dorothy Bishop on data sharing→

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But the one thing I've learned as I wiped the egg off my face is that error is inevitable and unavoidable, however careful you try to be. The best way to flush out these errors is to make the data public. This will inevitably lead to some embarrassment when mistakes are found, but at the end of the day, our goal must be to find out what is the case, rather than to save face.

Role models matter→

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This heartwarming story of junior high school students standing up for a classmate has been making the rounds—and also includes this important tidbit:

Andrews also says Desiree was inspired to try out for the cheerleaders' squad by watching an episode of the TV show Glee.

"They have a character with Down syndrome who is a cheerleader," he says. "And she said, 'If she can be a cheerleader, I can be a cheerleader.' "

Excerpt from Bill Watterson’s rare new "Calvin and Hobbes" interview→

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I honestly assumed that the books would go out of print within a few years, once they didn’t have the strip in the newspaper to create the readership for them. But people kept buying the books anyway, and now parents are showing them to their kids, and a new generation is coming up reading the strip. That’s something I never anticipated at all.

Guardian article summarizing kerfuffle over shoddy editorial practices

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In case you missed it, last month Dorothy Bishop wrote a blog post and a follow up highlighting what might charitably be described as "surprising" editorial practices. This Guardian article summarizes the sad state of affairs.

Matson isn’t the only academic to benefit from what might be generously referred to as an “extremely efficient” review process. Bishop’s analysis also identified other researchers who have published frequently in RIDD and RASD, including Jeff Sigafoos, Mark O’Reilly and Giuliano Lancioni. Bishop has provided data showing that for 73 papers appearing in RASD and RIDD co-authored by these researchers between 2010 and 2014, 17 were accepted the same day that they were received, 13 within one day, and 13 within two days. We contacted Sigafoos and Lancioni with this data, and they responded:

The figures you state for 73 papers is routine practice for papers published in RIDD and RASD. A large percentage of all papers published in any given issue of RIDD and RASD appear to have received a rapid rate of review as indicated would happen in the official editorial policy of these journals.

Kudos to Prof. Bishop and others for pointing out such shockingly appalling behavior.

A Compendium of Clean Graphs in R→

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Amazing resource from EJ Wagenmakers and Quentin Gronau. From the introductory blogpost:

]A] good graph obeys the golden rule: “create graphs unto others as you want them to create graphs unto you”. This means that a good graph is a simple graph, in the Einsteinian sense that a graph should be made as simple as possible, but not simpler. A good graph communicates the main message effectively, without fuss and distraction. In addition, a good graph balances its graphical and textual elements – large symbols demand an increase in line width, and these together require an increase in font size.

12 month MEG postdoc in Cambridge→

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Great opportunity to work at the Cognition and Brain Sciences Unit with Matt Davis.

Applications are invited for a post-doctoral scientist to join a team lead by Dr Matt Davis conducting cognitive neuroscientific research on speech processing. The primary objective of this position is to devise, implement, analyse and disseminate behavioural and brain imaging studies of speech perception and comprehension using Magneto- and Electro-encephalography (MEG/EEG). A particular focus will be studies that use time-frequency analyses of oscillatory neural responses, cerebro-acoustic coherence and acoustic decoding methods.

This is a 12 month position in which you will work on projects concerning prediction and expectation in speech perception and comprehension building on work initiated by staff on maternity leave.

John Ioannidis on scientific accuracy→

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Interesting interview from Vox with the author of "Why most published research findings are false" (and many other articles), including personal tidbits:

He even has a mythical origin story. He was raised in Greece, the home of Pythagoras and Euclid, by physician-researchers who instilled in him a love of mathematics. By seven, he quantified his affection for family members with a "love numbers" system. ("My mother was getting 1,024.42," he said. "My grandmother, 173.73.")

and thoughts on how to improve science:

Recently there’s increasing emphasis on trying to have post-publication review. Once a paper is published, you can comment on it, raise questions or concerns. But most of these efforts don’t have an incentive structure in place that would help them take off. There’s also no incentive for scientists or other stakeholders to make a very thorough and critical review of a study, to try to reproduce it, or to probe systematically and spend real effort on re-analysis. We need to find ways people would be rewarded for this type of reproducibility or bias checks.

The academic parent and "work-life balance"→

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Nice post from Aidan Horner.

The point I am trying to make is that a lot of talk about “balance” is directed towards cramming more stuff into the same number of hours. Instead I think we should talk more openly about what is and what isn’t important. What we can give up and what we need to maintain. Only then should we discuss how we can use the finite number of hours allotted to us to carry out the tasks that we have prioritised.