Artificial Intelligence and JM Rejections
by ELMAR Moderator
Ian Wilkinson seeks rejection letters, associated reviews and the submitted paper for manuscripts rejected by the Journal of Marketing. He aims to perform an Artificial Intelligence Informed Analysis of the results.
Date: Sat, 24 Dec 2005 11:17:45 +1100
From: Ian Wilkinson <firstname.lastname@example.org>
Subject: REQUEST: Artificial Intelligence and JM Rejections
An Artificial Intelligence Informed Analysis of Rejection Letters and Associated Reviews of the JM We are beginning a study of important texts in the discipline of marketing that affect us all and play a major role in the evolution of our discipline, namely rejection letters and associated reviews for papers rejected by the JM plus the
paper rejected. A data base is being assembled and we seek contributions to ensure our data base is not biased towards particular researchers or topics. All contributors will be acknowledged in the publications arising from this project. The methodology is as follows:
Step 1: Assemble a data base of rejection letters, associated reviews and the submitted paper for papers submitted to JM. Desk rejections can also be included but generally the amount of information provided is limited and this will inhibit analysis. We need information of date of submission, number of rounds of reviews, date of rejection letter, academic level of authors, university and country where authors received their Phd (if relevant), university at time of submission, ethnic origins of authors and other pertinent information in order to tag each contribution to our database. I have made a significant donation to the data base and some of my friends and colleagues have promised sizeable donations but we seek a wider cross section to be more representative of non success. We may include a control sample of accepted papers.
Step 2: Once a viable number of cases have been collected they will be analysed using a recently developed Australian AI tool for parsing text into underlying concepts and for mapping relations between these concepts. The tool was showcased at a special session of the recent annual conference of the Australia New Zealand Marketing Academy held in Fremantle. Tags or labels can be applied to reflect different types of submissions such as country of origin, year, academic level of first author etc. The method provides a robust and reproduceable analysis of the underlying patterns in the data.
Step 3. A publication reporting the results will be submitted to the JM
Step 4a. If accepted we will have to draw the project to an end and celebrate our success. We will then turn our attention to other journals and nominations are welcome.
Step4b. If rejected we add the results to our database and return to Step 1.
Thank you for your attention and I look forward to receiving your donations.
Donations should be sent to:
Professor Ian F. Wilkinson
School of Marketing
University of New South Wales Australia
Phone: 61-2-9385 3298
Fax: 61-2-9663 1985