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Thursday, 21 February 2019

11:00 PM

Threat models for open online scientific engagement? [Living in an Ivory Basement] 11:00 PM, Thursday, 21 February 2019 02:00 PM, Thursday, 06 August 2020

(Thanks to Matthew Turk, Rebecca Calisi, Karen Word, Amanda Charbonneau, and Rayna Harris for their excellent suggestions and comments on drafts of this blog post, and to Tracy Teal for many discussions of this issue over the years! And special thanks to Olivia Guest for being a great person to follow on Twitter in general, and more specifically in this regard!)

My goal (and that of many others in the open science space) is to help advance science by finding ways to make it more open, diverse, and inclusive - both by promoting open science methods, and by improving diversity, equity and inclusion in scientific communities. In recent years this has led to some great advances in my area of science, including preprints coming to biology, increasing adoption & enforcement of codes of conduct in workshops, and dramatic improvements in gender ratios for some conferences.

But not everyone wants to or feels they can participate in open science approaches. I'm interested in clearly identifying reasons why people feel this way, so that we can do our best to mitigate and address these reasons.

In this context, I was thinking this morning about the various impediments to scientists that want to build their reputation through online interaction. I know from listening to people in person and on Twitter that many scientists are quite hesitant to engage on Twitter and blogs because of the many known and expected negatives.

One warning - some people may find this line of thought depressing or anxiety inducing, and you may not want to read on! My goal is to improve the situation by confronting and exploring the negatives so that we can mitigate them. (I think the positives have been discussed in detail.)


A draft catalog of threats or consequences to online scientific interaction.

I know people have written in detail about specific reasons or situations, but my naive Google searches don't find a catalog, and it seems like that would be useful! Pointers to catalogs or lists I've missed would be welcome!

Below is my initial list - feedback welcome, either via e-mail (titus@idyll.org) or in comments. Stories are also welcome. I'm happy to anonymize and/or receive anonymous e-mails!

I've ordered the list from what I think is "least severe" to "most severe".

1. Diversion of effort and attention

Online engagement takes time!

  • Twitter and blogging etiquette are confusing and take considerable time (and engagement) to understand.
  • People may respond and engage you in unexpected diversions that significantly expend your time.

2. Intellectual theft

Discussing ideas and/or providing data openly may lead to intellectual theft.

Specifically,

  • Research idea theft (e.g. taking ideas for a specific or general research plan without attribution or collaboration).
  • Methods theft (e.g. reusing source code or data analysis notebooks without attribution or collaboration).
  • Data theft (e.g. making use of public data without appropriate attribution or collaboration).
  • Scooping (e.g. competitors speeding up publication of their work based on disclosure of your work).

3. Reputational impact

Revealing information about your ideas, analyses, or data opens you up to reputational attack in visible ways. It also opens you up to the charge that you are wasting your time because online engagement is "unserious".

Specifically,

  • uninformed/incorrect criticism of your research that convinces others that your research is problematic.
  • your research may be taken out of its intended context, accurately or inaccurately.
  • informed criticism that reveals potential flaws in your project.
  • discovery of outright errors (data errors, analysis errors).
  • accusations of insufficient rigor, e.g. "you are not posting your code to github, so you are a bad scientist."
  • posting draft thoughts that are revealed to be inaccurate or incomplete.
  • accusation of intellectual theft (e.g. incorrect accusations of you having stolen ideas/data/code, based on similarities in methodology revealed by online/open engagement).
  • accusations that you are expending your time unwisely and hence are not sufficiently "serious". (This is typically an accusation made by senior academics.)

4. Professional retaliation

Revealing information about your research (ideas, analyses, or data) or research-related activities (peer review) opens you up to professional retaliation, in ways that might be invisible or hard to detect.

Specifically,

  • unfair / personally motivated negative grant and paper reviews.
  • negative interviews, hiring reviews, or tenure letters.
  • your boss or someone in your administrative line may disagree with your opinions and retaliate privately.

5. Harassment, targeted or general

Putting yourself out there means that you might be harassed, in either a targeted way or in a general way.

Specific examples:

  • personal harassment (private or public, e.g. brigading or persistent 'splaining).
  • harassment via employer (contacting your employer or professor to complain about you).
  • doxxing or otherwise revealing personal information online, that may have adverse personal or academic consequences, including physical threats.

I'm sure I'm missing a lot - would love to know what you think!

It's clear that many of these disproportionately affect people who are already in precarious positions, which is something I'm interested in exploring more. For one specific example, harassment is (very) frequently gendered or ethnic harassment, so this disproportionately affects women, the underrepresented, and LGBTQ, among others. I am certain this dramatically affects the diversity of people who engage online, with both strong direct negative impacts and loss of possible reputational enhancement.

I think it's particularly challenging to realize how many of these are double-edged swords. For example, I love finding out about flaws in my project or code, because that enables me to correct them (the "fail fast" mentality of open source projects); but that is unlikely to negatively impact my employment, since I'm a quite senior white gentleman with tenure. This is far more likely to negatively impact someone who is junior; they may be remembered as "that person who was proven wrong about something obvious."

--titus

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