Examples
Worked examples
- Is an instance
A bibliometric analyst reports FWCI with confidence intervals and the underlying article count.
- Is an instance
A funder uses FWCI as one input among several in portfolio-level analysis, not in individual decisions.
Counter-examples
Looks similar, but isn't
- Not an instance
Comparing FWCI of two researchers with very different output counts as if statistically equivalent.
- Not an instance
Setting FWCI > 1.0 as a hiring threshold.
Editorial commentary
FWCI was developed to enable comparison of citation performance across disciplines and time. An FWCI of 1.5 means an article has received 50% more citations than the average of comparable items globally. While field normalisation is methodologically preferable to raw counts or unnormalised journal metrics, FWCI still inherits database-dependence (Scopus coverage), classification assumptions (the field categorisation used as denominator) and aggregation pitfalls when averaged at researcher or institution level. Responsible-metrics guidance recommends FWCI be reported alongside underlying counts, with sample-size caveats.
References
- Elsevier SciVal documentation. Waltman L 'A review of the literature on citation impact indicators' Journal of Informetrics 2016.
Also known as
FWCI · Field-weighted citation impact
Machine-readable encodings
Use in your systems
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