Research peer review/Bibliography

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• Smith RW. In search of an optimal peer review system. J Participat Med. 2009(Oct);1(1):e13.
• Frishauf P. Reputation systems: a new vision for publishing and peer review. J Participat Med. 2009(Oct);1(1):e13a.
• Gordon, R. & B.J. Poulin (2009), "Cost of the NSERC Science Grant Peer Review System Exceeds the Cost of Giving Every Qualified Researcher a Baseline Grant", Accountability in Research 16 (1): 13–40, DOI:10.1080/08989620802689821 ^[e]

Suggests, based on a study of the costs of peer review at the Natural Sciences and Engineering Research Council of Canada, that innovation could be stimulated by avoiding peer review for grants at the initial stages of research.

• Spier, R. (2002), "The history of the peer-review process", Trends Biotechnol 20 (8): 357–8, DOI:10.1016/S0167-7799(02)01985-6
• Jefferson T, Wager E, Davidoff F (2002). "Measuring the quality of editorial peer review". JAMA 287 (21): 2786-90. PMID 12038912. ^[e]

• Rothwell PM, Martyn CN (2000). "Reproducibility of peer review in clinical neuroscience. Is agreement between reviewers any greater than would be expected by chance alone?". Brain 123 ( Pt 9): 1964-9. PMID 10960059. ^[e]

• Campanario, J.M. (1996), "Have referees rejected some of the most-cited articles of all times?", Journal of the American Society for Information Science 47 (4): 302–310
• Judson, H. F. (1994), "Structural transformations of the sciences and the end of peer review", JAMA: The Journal of the American Medical Association 272 (2): 92–4, DOI:10.1001/jama.272.2.92
• Burnham, J. C. (1990), "The evolution of editorial peer review", JAMA: The Journal of the American Medical Association 263 (10): 1323–9, DOI:10.1001/jama.263.10.1323
• Cole S, Cole JR, Simon GA (1981). "Chance and consensus in peer review". Science 214 (4523): 881-6. DOI:10.1126/science.7302566. PMID 7302566. Research Blogging. ^[e]

Summary: "An experiment in which 150 proposals submitted to the National Science Foundation were evaluated independently by a new set of reviewers indicates that getting a research grant depends to a significant extent on chance. The degree of disagreement within the population of eligible reviewers is such that whether or not a proposal is funded depends in a large proportion of cases upon which reviewers happen to be selected for it. No evidence of systematic bias in the selection of NSF reviewers was found."

• Ellsberg, Daniel (1961), "Risk, Ambiguity, and the Savage Axioms", Quarterly Journal of Economics 75 (4): 643–669, DOI:10.2307/1884324 ^[e]

Introduces the Ellsberg paradox, a phenomenon studied in decision theory and relevant, for instance, for risk assessment during peer review of research grant proposals.