Monday, 9 November 2015

New publications on peer reivew

Casnici N., Grimaldo F., Gilbert N. and Squazzoni F. (2015) Attitudes of referees in a multidisciplinary journal: An empirical analysis, JASIST (Journal of the Association for Information Science and Technology), forthcoming

Bianchi F. and Squazzoni F. (2015) Is Three Better Than One? Simulating the Effect of Multiple Reviewer Selection on the Quality and Efficiency of Peer Review, Ylmaz et al. (Eds), Proceedings of the 2015 Winter Simulation Conference

Cowley S. (2015) How peer review constrains cognition: on the frontline in the knowledge sector, Frontiers in Psychology

Nedić O. and Dekanski A. (2015) A survey on publishing policies of the Journal of the Serbian Chemical Society – On the occasion of the 80th volume, The Journal of the Serbian Chemical Society, 959-969, 2015

Caram L.F., Caiafa C. F., Ausloos,M. and Proto A. N. (2015) Cooperative peer-to-peer multiagent-based systems, Physical Review E, E 92, 022805

Huutoniemi K. (2015) Interdisciplinarity as Academic Accountability: Prospects for Quality Control Across Disciplinary Boundaries, Social Epistemology A Journal of Knowledge, Culture and Policy (DOI:10.1080/02691728.2015.
As collected by the PEERE COST action.

Thursday, 5 November 2015

Paper: Reviewer Fatigue? Why Scholars Decline to Review their Peers’ Work

This paper reports the results of a survey of academics about their attitudes and experiences of peer review.

Reviewer Fatigue? Why Scholars Decline to Review their Peers’ Work

Marijke Breuninga1, Jeremy Backstroma2, Jeremy Brannona1, Benjamin Isaak Grossa1 and Michael Widmeiera1

a1 University of North Texas
a2 National Consortium for the Study of Terrorism and the Responses to Terrorism (START)


As new academic journals have emerged in political science and existing journals experience increasing submission rates, editors are concerned that scholars experience “reviewer fatigue.” Editors often assume that an overload of requests to review makes scholars less willing to perform the anonymous yet time-consuming tasks associated with reviewing manuscripts. To date, there has not been a systematic investigation of the reasons why scholars decline to review. We empirically investigated the rate at which scholars accept or decline to review, as well as the reasons they gave for declining. We found that reviewer fatigue is only one of several reasons why scholars decline to review. The evidence suggests that scholars are willing to review but that they also lead busy professional and personal lives.

The paper is at:

Wednesday, 4 November 2015

Paper modelling the impact of possible EU research funding policies

Ahrweiler, Petra, Schilperoord, Michel, Pyka, Andreas and Gilbert, Nigel (2015) 'Modelling Research Policy:  Ex-Ante Evaluation of Complex Policy Instruments' Journal of Artificial Societies and Social Simulation 18 (4) 5 <>. doi: 10.18564/jasss.2927


This paper presents the agent-based model INFSO-SKIN, which provides ex-ante evaluation of possible funding policies in Horizon 2020 for the European Commission’s DG Information Society and Media (DG INFSO). Informed by a large dataset recording the details of funded projects, the simulation model is set up to reproduce and assess the funding strategies, the funded organisations and projects, and the resulting network structures of the Commission’s Framework 7 (FP7) programme. To address the evaluative questions of DG INFSO, this model, extrapolated into the future without any policy changes, is taken as an evidence-based benchmark for further experiments. Against this baseline scenario the following example policy changes are tested: (i) What if there were changes to the thematic scope of the programme? (ii) What if there were changes to the instruments of funding? (iii) What if there were changes to the overall amount of programme funding? (iv) What if there were changes to increase Small and Medium Enterprise (SME) participation? The results of these simulation experiments reveal some likely scenarios as policy options for Horizon 2020. The paper thus demonstrates that realistic modelling with a close data-to-model link can directly provide policy advice.