Open Science Theory

A number of contemporary forces have conspired to drive highly-competent academics away from the academy. The vagaries of departmental hiring, institutional conservatism, and growth in the number of researchers versus available positions have displaced talent and innovation. Enter the alt-academic institution: small-scale institutions engaged in academic research in niche areas that are not viable at conventional institutions. I will introduce the reader to a specialized type of alt-academic institution by discussing their economics, organizational structure, and approach to collaboration/mentorship. Additionally, innovations such as infrastructural innovation, open access pipelines with version control, heterarchical organization, and a flexible contribution philosophy have made such institutions possible. The main subjects for this point of view article will be the OpenWorm Foundation (http://openworm.org/) and the Orthogonal Research and Education Laboratory (https://orthogonal-research.weebly.com/). Readers are also provided with an account of institutional challenges, from article/book access to encouraging collaborative participation. As recent financial crises and pandemics have made clear, we need robust alternative institutions to overcome challenges to the pure research enterprise. Distributed virtual alt-academic institutions can also serve to increase diversity and overall participation in the research enterprise. This has positive consequences for science literacy and discovery more generally.

Progress in scientific fields is usually thought to consist of formulating testable hypotheses and initiating paradigm shifts. Both of these views exclude the content of scientific fields that lead to milieu in which hypotheses and paradigms are formed. Therefore, it is proposed that a new view of scientific fields called coherence-based relevance be used to take into account the intellectual content of theories and how that can affect our view of both the history of science and the empirical world. The argument can be summarized by the argument that as scientific fields emerge, they are shaped by three forces: the historical contingency of the new field, the pattern of co-authorship and intellectual affinities within the field, and the salience of key references and citations within this social network. In this paper, the first two points will be tested with data (words from titles and abstracts) from selected journals and conference proceedings for four specific cases. When the same terms are used over time, it is indicative of stasis in terms of what is viewed as relevant in the field. A lack of similarity over time suggests a field in flux, at least in terms of relevant topics, theories, and methods. These results will be discussed, as well as the relationship between relevance, conceptual coherence, and changes in scientific practice over time.

Presentation on Theory-building techniques and their relative importance in the field of Data Science.

A semi-supervised model of peer review is introduced that is intended to overcome the bias and incompleteness of traditional peer review. Traditional approaches are reliant on human biases, while consensus decision-making is constrained by sparse information. Here, the architecture for one potential improvement (a semi-supervised, human-assisted classifier) to the traditional approach will be introduced and evaluated. To evaluate the potential advantages of such a system, hypothetical receiver operating characteristic (ROC) curves for both approaches will be assessed. This will provide more specific indications of how automation would be beneficial in the manuscript evaluation process. In conclusion, the implications for such a system on measurements of scientific impact and improving the quality of open submission repositories will be discussed.