Coherency Models of Review Judgements

I am at a nice interdisciplinary workshop in Berlin on "Coherency-Based Approaches to Decision Making, Cognition and Communication.

The basic ideas come from Thagard (1989), that human 'reasoning' happens in a way to ensure coherency between beliefs rather than the classical logicist picture of reasoning from evidence to conclusions.  For example, as well as forward inference, backward inference from conclusions to the evaluation of evidence is common. This theory has now a reasonable amount of evidence to support it and has been extended to include emotions and goals (Thagard 2006)

As well as Thagard there was a nice talk by Dan Simon of University of South Carolina, explaining many identified 'biases' in human reasoning using the coherency framework. If you want details see his paper on SSRN at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=439984. One of the biases he talked about was confirmation bias and cited a nice paper that I did not know about about Peer Review.  This is:

Mahoney, M (1977) Publication prejudices: An experimental study of confirmatory bias in the peer review system. Cognitive Therapy and Research, 1(2):161–175. http://link.springer.com/article/10.1007/BF01173636. 

 In this the author sent papers to a selection of reviewers where it was known whether the reviewer agreed or disagreed with the conclusion of the paper (on a controversial issue). The results were that the judgement of the reviewers on the quality of the paper were substantially affected by whether the reviewer agreed with the conclusion.

The coherency model of thought seems to be a good basis for modelling the judgement of reviewers within simulations of the peer review system.

CfP special issue on "Academic Misconduct & Misrepresentation: From Fraud and Plagiarism to Fake Peer Reviews, Citation Rings, Gaming Rankings, Dodgy Journals, “Vacation” Conferences, and Beyond"

in the journal: Research Policy

Edited by: Mario Biagioli and Martin Kenney

This Special Issue solicits social scientific articles examining not only traditional forms of misconduct, but also modalities of misconduct that are meant to “game” the modern metrics-based regimes of academic evaluation.  If traditional misconduct – fabrication, falsification, and plagiarism – concerned fraudulent ways to produce scholarly publications, much of the new misconduct targets the publication system itself, for example by producing fake peer reviews, citation rings among authors and journals, or by publishing articles in dubious journals. 

...

See http://www.journals.elsevier.com/research-policy/call-for-papers/academic-misconduct-misrepresentation-from-fraud-and-plagiar for more details.

Nature paper: Interdisciplinary research has consistently lower funding success

 See http://www.nature.com/nature/journal/v534/n7609/full/nature18315.html

"...we show that the greater the degree of interdisciplinarity, the lower the probability of being funded. The negative impact of interdisciplinarity is significant even when number of collaborators, primary research field and type of institution are taken into account."

x axis is the proportion of applications funded (Australian research council) and the y-axis is the estimated bias towards interdisciplinary proposals (estimated using a logit regression model).

Environmental, physical, social science and economics were (unsurprisingly) most averse to interdisciplinary proposals.

Repost: Why publishing negative findings is hard

From retraction watch, the story of a professor who tried to submit his reanalysis of two papers to journals and the obstacles he faced.

At: http://retractionwatch.com/2016/02/17/why-publishing-negative-findings-is-hard/

Abstract of Paper: Job Insecurity in Academic Research Employment: An Agent-Based Model

Abstract:

This paper presents an agent-based model of fixed-term academic employment in a competitive research funding environment.  The goal of the model is to investigate the effects of job insecurity on research productivity.  Agents may be either established academics who may apply for grants, or postdoctoral researchers who are unable to apply for grants and experience hardship when reaching the end of their fixed-term contracts.  Results show that in general adding fixed-term postdocs to the system produces less total research output than adding half as many permanent academics.  An in-depth sensitivity analysis is performed across postdoc scenarios, and indicates that promoting more postdocs into permanent positions produces significant increases in research output.

More details at:  https://drericsilverman.wordpress.com/2016/03/03/paper-submitted-to-alife-xv/

Network analysis paper: Weaving the fabric of science: Dynamic network models of science's unfolding structure

Weaving the fabric of science: Dynamic network models of science's unfolding structure

By Feng Shi, Jacob G. Foster, and James A. Evans

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Highlights

• Our hypergraph framework captures the multi-mode, higher-order complexity of science.

• Our random walk model powerfully predicts how science evolves.

• Our approach reveals intriguing modal dispositions behind the advance of science.

• We find that entities of one type typically connect through entities of another type.

• We find a special bridging role for methods and chemicals in the fabric of science.

• We find that adding more node types leads to superlinear improvements in prediction.

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Abstract

Science is a complex system. Building on Latour's actor network theory, we model published science as a dynamic hypergraph and explore how this fabric provides a substrate for future scientific discovery. Using millions of abstracts from MEDLINE, we show that the network distance between biomedical things (i.e., people, methods, diseases, chemicals) is surprisingly small. We then show how science moves from questions answered in one year to problems investigated in the next through a weighted random walk model. Our analysis reveals intriguing modal dispositions in the way biomedical science evolves: methods play a bridging role and things of one type connect through things of another. This has the methodological implication that adding more node types to network models of science and other creative domains will likely lead to a superlinear increase in prediction and understanding.

Keywords

Link prediction; Hypergraphs; Random walks; Multi-mode networks; Science studies; Metaknowledge

Paper (open access) available at: http://www.sciencedirect.com/science/article/pii/S0378873315000118

Modelling academic research funding as a resource allocation problem

OK this is 5 years old but I have only just come accross it. From 2010 but modified 2014.

Geard, Nicholas and Noble, Jason (2010) Modelling academic research funding as a resource allocation problem. In, 3rd World Congress on Social Simulation, University of Kassel, Germany, 06 - 09 Sep 2010. (Submitted). 

Abstract:

Academic research funding is allocated through a competitive bidding process that may lead to inefficiency as excessive time is spent on proposal writing. We develop a simple agent-based model of the process and find that current systems are indeed likely to be inefficient. Alternative allocation schemes involving either a cap on individual effort or appraisal from the centre are indicated as improvements.

For code and paper see:  http://eprints.soton.ac.uk/271374/