Technology is inevitably changing how scientists interact with journals and, ultimately, with each other. Consider workshops such as BeyondthePDF2 and platforms hosting primary literature discussion such as Journal Lab. If this is the future, how can graduate students find security in future incentives with subjectively “classical” contributions? By re-evaluating the assessment criteria and the process of dissemination for scientific findings in a technological age, we can work identify the gaps in scientific discourse that need to be filled.
Graduates are confronted with using new approaches to scientific discourse while maintaining previous Gutenberg-inspired methods (e.g. paying publishers to sell it, paying more for color photos when ink is no longer an issue, etc.) . Chris Holdraf writes an insightful overview to how training in graduate school is shaping the world beyond the walls of academia in his article Beyond Academia: a new approach to PhDs. Future jobs for scientists include the possibility of filling in these gaps, and science hubs and blogs are becoming epicenters for real-time data sharing and discussion, like platforms being established by PLOS, for instance.
Another change to consider is to incentivize well-conducted and ethical null results with publications, rather than drive the production of sloppy novel findings that take decades to remove from mass-media and debunk (vaccination and autism being a classic example). Noopur Amin, a post-doctoral researcher in the lab of Daniela Kaufer, shared with me data-sharing sites for electrophysiology and neuroimaging as well as the resources shared in a paper from Nature Methods addressing the importance of open-access repositories for behavioral data.
From Fonio et al., 2012:
“A collection of data related to behavioral measurements of individual animals acquired in multiple laboratories, at multiple times, involving multiple strains, and with no out-of-the-way standardization efforts could be a resource of great value for evaluating the validity of different behavioral measures. Such databases have been established in recent years: for example, the EuroPhenome database , the WebQTL’s Published Phenotypes database and the Mouse Phenome Database. Although these as yet include only a limited number of laboratories and genotypes, they all try to enlist larger groups of researchers and to expand the animal models covered, and they are publicly available. It will be beneficial for the redesign of new behavioral measures that raw behavioral data will be available as well in these databases. Access to this information will allow experimenters to extract from the database the size of the genotype-by-laboratory interaction relevant to their experiment. The experimenters can then conduct their work in their own laboratory and combine their in-lab variability with the outside information on interaction variability, which will help them obtain more realistic estimates of variance. It is reassuring to observe the coordinated efforts going into the construction of the database, but more effort is required to develop the analysis tools needed for the use of the databases for the above purpose.”
What it boils down to is an oxymoron (in jest, of course): social academia.
Academics scratch the technological interface with social media like Mendeley and Academia, only to update their CV when they are on the verge of applying for jobs*, not so much for soliciting feedback or facilitating collaborations.
At conferences, when scientists have the opportunity to share and solicit feedback, it can get awkward. “I did the same study 20 years ago, this is not novel!” or “Did you control for that?” can send shivers up a young scientist’s spine.
The sociology of science is a consideration when shaping future of scientific discourse. The Annual Meeting of the Society for Social Studies of Science (4S) is a conference to address these non-trivial issues. For example, what should the purpose of a conference even be? Should journal publications be peer-reviewed by just four anonymous shadows, that are subject to waking up on the wrong side of the bed just like the rest of us? Perhaps I am going overboard with my expressions here.
Technology is indeed shaping how we interact with primary literature. Will everyone be illustrating data in interactive and dynamic ways shown in this TED talk series? Is this form of data visualization more informative than bar graphs, or can this be abused to mask poorly collected data? There are many considerations to make and too little time for this blog entry. Feel free to expand on this and share your thoughts in the comments section.
In any case, the abstract submission for the 4S conference is March 17th. It’s in San Diego. Here are some cool open sessions that caught my eye that may interest you:
2. Neurotechnologies, Neuroethics, and Neuro-identities
5. STS Perspectives on Parenting
Susan Kelly; Michelle McGowan
8. Is Resistance Futile? Adventures in Resisting the Big Data Bandwagon (or Assimilating, If You Must)
20. Academic Conference Cultures and Presentation Practices
21. Reopening the Black Box of Academic Journals
Didier Torny; David Pontille
27. Competition and Collaboration in Scientific Research – Revisited
Diana Schmidt-Pfister; Nora Hangel
30. Affect, Emotion, and Digital Media
34. Machine Learning Worlds: Politics and Practices
Shreeharsh Kelkar; Goede Both
39. Creating Dialogues in Science Communication: Methodology and Practices
Yuko Murakami; Miwa Kuri
41. STS and Social Inequality: The Role of Gender, Race and Class in Career
Simon Nicholas Williams; Christine Wood
44. The Cloud and the Crowd
Cori Hayden; Nicholas D’Avella
45. Doing Research, Meddling with Power. On the Contradictory Engagements of STS with Politics and Normativities.
Thomas Voelker; Claudia Schwarz; Simone Schumann; Andrea Schikowitz; Gernot Rieder; Michael Penkler; Judith Igelsboeck; Kay Felder; Dorothea Born
(Click here for the full list.)
*(or just to productively procrastinate)
Image courtesy Decaseconds Photography.