Dataset of Journal Publications about Peace on Web of Science 2015 to 2018
This dataset tracks journal publications about peace on Web of Science from 2015 to 2018 and is coded by country of author's affiliation, country of publication, and countries studied.
Authorship
This dataset was compiled as part of a research project conducted by Anna Johnson, Josephine Lechartre, Sehrazat Mart, Mark Robison, and Caroline Hughes at the Kroc Institute of International Peace Studies. Work on designing and compiling the dataset was led by Noah Imel. This research was funded by the Kroc Institute for International Peace Studies.
Description
The dataset comprises a complete set of journal publications in Web of Science from 2015 to 2018 that have a substantive concern with the concept of peace as this is studied in the field of Peace Studies.
Criteria for Inclusion in the Dataset
The primary criterion for inclusion was that the keyword "peace" appears in the publication title or abstract. A search on Web of Science was conducted to identify these publications.
In order to determine whether peace was dealt with in a substantive way, search results generated were then cleaned through an iterative process of examining the results to identify types of usage of the term "peace" that are not substantive or pertinent to the field of peace studies.
This led to the establishment of criteria for exclusion as follows:
- "peace" refers to a proper noun (eg. the Peace River);
- "peace" refers to an acronym (eg. Posthumous Evaluation of Advanced Cancer Environments);
- "peace" is used to refer to "peace of mind" in medical settings (i.e. as confidence in medical procedures); or
- "peace" is used as a shorthand to describe a period of time (i.e. Winston Churchill in War and Peace), but the nature of peace in the era concerned is not an object of study.
We acknowledge that there may be articles that might appropriately be considered as contributing to the field of peace studies, but that do not include the word "peace" in the title or abstract. In particular, there may be articles that focus more squarely on concepts of violence, conflict, or war that would be of interest to peace studies scholars. However, we contend that a defining feature of peace studies, that separates it from, for example, security studies or war studies, is that it studies violence and warfare not in and of itself, but in relation to peace. Therefore, we contend that the resulting dataset offers a suitable proxy for analysis of patterns of authorship and publication within the field of peace studies as hosted by Web of Science.
Why Web of Science?
The version of Web of Science used for this project includes the Emerging Sources Citation Index, which incorporates publications from a wider diversity of countries. We acknowledge that a plethora of scholarship relating to peace is ongoing in many different contexts, but does not make it into Web of Science. In compiling the dataset, we hope to make explicit the limitations to the field as represented by Web of Science, since Web of Science has come to signify a particular hegemonic conception of rigor and quality in scholarship. Our project investigates what patterns of publication within Web of Science might be able to tell us about the barriers faced by scholars in different parts of the world in participating in a global scholarly conversation about peace, and how we might begin breaking down these barriers.
Description of Columns Added to Data
Columns A, M-Y and AC-BM show data downloaded from Web of Science.
Columns were added in creating the dataset, as follows:
- Column B: unique identifying number within dataset
- Column C: three-letter code to identify country of affiliation of author. Where more than one country of affiliation is associated with an authorial team, the publication appears in the dataset once for each country of affiliation represented. Searching by unique identifying number will identify all iterations of the piece within the dataset.
- Column D: three-letter code to identify the income level of the country of affiliation listed in Column C. The income level categories used are taken from the World Bank. Complete data for 2018-19 and information about income thresholds can be found at https://blogs.worldbank.org/opendata/new-country-classifications-income-level-2018-2019. There are four categories as follows: High Income (HIC), Upper-Middle Income (UMC), Lower Middle Income (LMC), and Low Income (LIC).
- Column E: Place of publication: this refers to the location of the publishing house (for example, Taylor and Francis or Routledge) rather than to the location of the editorial board of the journal
- Column F: Income level of the country of publication listed in Column E
- Column G: Type of publication: J = journal article, P = conference proceedings, B = book review
- Column H: Articles are coded to show whether they are single-authored (S) or co-authored (C). Where articles are single-authored by an author with multiple country affiliations, the first affiliation is coded (S) and subsequent affiliations are coded (SX). Where articles are co-authored by several authors with multiple country affiliations, the first author’s first affiliation is coded (C) and subsequent affiliations are coded (X). By filtering on this column, repeat iterations of an article can be hidden.
- Column I: Co-authored articles where multiple countries of affiliation are incorporated in the authorial team are coded for type of collaboration. Four types of collaboration are identified. North-North Collaboration (NNC) refers to collaboration between two or more high-income countries. North-South Collaboration (NSC) refers to collaboration between one or more high-income countries and one or more upper-middle, lower-middle or low-income countries. Triangular Collaboration (TC) refers to collaboration between one or more high-income countries and at least two upper-middle, lower-middle or low-income countries. South-South Collaboration (SSC) refers to collaboration between two or more upper-middle, lower-middle or low-income countries with no high-income-affiliated authors involved. Single-authored articles or co-authored articles in which only one country of affiliation is involved are not coded in this column.
- Column J: Three-letter codes indicate all the countries of affiliation incorporated in the authorial team for co-authored articles
- Column K: Three-letter codes indicate the income levels of all the countries of affiliation incorporated in the authorial team for co-authored articles
- Column L: Three letter codes indicate where an individual author has multiple affiliations with more than one country
- Column Z: Three-letter codes indicate countries mentioned by name in the title or abstract of the article
- Column AA: Three-letter codes indicate the income-levels of countries mentioned by name in the title or abstract of the article
- Column AB: A figure 1 in this column indicates that the abstract of the article makes claims to theory-building or theory-testing