The DOI matches its Crossref record.
A Co-Citation Model of a Scientific Specialty: A Longitudinal Study of Collagen Research
Abstract
The phenomenon of specialization in science is receiving increasing attention as it becomes clear that the 'specialty' is the principal mode of social and cognitive organization in modern science. Recently, there have been some attempts to formulate theories of specialty growth and change.' Before sufficient evidence can accumulate to confirm or refute these theories, it seems likely that systematic and consistent methodological frameworks must be developed. The specialty of collagen research is presented here as the vehicle for exploring the possibilities of one such methodology. Collagen research was selected because its recent history illustrates what is possibly an important type of specialty change -- namely, that of rapid shift in research focus, or what might be loosely termed 'revolutionary' change. In this paper I outline a general method for the study of specialty change, based upon citation data. The point of departure is a system which clusters highly cited documents, using their frequency of cocitation as a measure of association.2 This system uses the magnetic tape version of the Science Citation Index (SCI) as its data base. The clusters obtained from the SCI have been found to correspond to narrow subject matter groupings and it has been suggested that these reflect the social and cognitive structures of research specialties. The collagen specialty was selected from roughly 1,000 clusters identified by applying this algorithm to the SCI.3
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Searching for intellectual turning points: progressive knowledge domain visualization
Chen, C. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307513100 · Cited by 2,791
From translations to problematic networks: An introduction to co-word analysis
Callon, M., Courtial, J.-P., Turner, W. A., & Bauin, S. (1983) · Social Science Information · doi:10.1177/053901883022002003 · Cited by 1,951
Metadata
- Authors
- Small, H. G.
- Venue
- Social Studies of Science
- Publisher
- SAGE Publications
- Published
- 1977-05
- Volume
- 7
- Issue
- 2
- Pages
- 139-166
- ISSN
- 0036-8539 (ISSN-L)
- 0306-3127
- 1460-3659
- OpenAlex
- W1992724014
- Cited by
- 270
- References
- 0
- FWCI
- 13.04
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.