The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
On Quantitizing
Open accessAbstract
Quantitizing, commonly understood to refer to the numerical translation, transformation, or conversion of qualitative data, has become a staple of mixed methods research. Typically glossed are the foundational assumptions, judgments, and compromises involved in converting disparate data sets into each other and whether such conversions advance inquiry. Among these assumptions are that qualitative and quantitative data constitute two kinds of data, that quantitizing constitutes a unidirectional process essentially different from qualitizing, and that counting is an unambiguous process. Among the judgments are deciding what and how to count. Among the compromises are balancing numerical precision with narrative complexity. The standpoints of ``conditional complementarity,'' ``critical remediation,'' and ``analytic alternation'' clarify the added value of converting qualitative data into quantitative form.
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
Cites
Three Approaches to Qualitative Content Analysis
Hsieh, H.-F., & Shannon, S. E. (2005) · Qualitative Health Research · doi:10.1177/1049732305276687 · Cited by 44,601
Ontological Relativity and Other Essays
Quine, W. V. (1969) · doi:10.7312/quin92204 · Cited by 3,593
Understanding and Validity in Qualitative Research
Maxwell, J. (1992) · Harvard Educational Review · doi:10.17763/haer.62.3.8323320856251826 · Cited by 2,951 · cited 1×
“…moves to clean up the messiness of interview data: to reduce them in a way that optimizes both the descriptive and interpretive validities (Maxwell, 1992) prized in qualitative research (i.e., getting the ‘‘facts’’ and the actors’ points of view right) and the internal validity prized in…”
BackgroundSelf-reports: How the questions shape the answers.
Schwarz, N. (1999) · American Psychologist · doi:10.1037/0003-066x.54.2.93 · Cited by 2,846
Cohen, J. (1983) · Applied Psychological Measurement · doi:10.1177/014662168300700301 · Cited by 1,564
Cited by
What's in a name? Qualitative description revisited
Sandelowski, M. (2010) · Research in Nursing & Health · doi:10.1002/nur.20362 · Cited by 4,975
Self-citationUsing Numbers in Qualitative Research
Maxwell, J. A. (2010) · Qualitative Inquiry · doi:10.1177/1077800410364740 · Cited by 985
How to Conduct a Mixed Methods Study: Recent Trends in a Rapidly Growing Literature
Small, M. L. (2011) · Annual Review of Sociology · doi:10.1146/annurev.soc.012809.102657 · Cited by 829
Triangulation and Mixed Methods Designs: Data Integration With New Research Technologies
Fielding, N. G. (2012) · Journal of Mixed Methods Research · doi:10.1177/1558689812437101 · Cited by 447
Silver, M. P. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3588 · Cited by 224
Metadata
- Authors
- Sandelowski, M., Voils, C. I., & Knafl, G.
- Venue
- Journal of Mixed Methods Research
- Publisher
- SAGE Publications
- Published
- 2009-04-21
- Volume
- 3
- Issue
- 3
- Pages
- 208-222
- ISSN
- 1558-6898 (ISSN-L)
- 1558-6901
- OpenAlex
- W4241124503
- Cited by
- 646
- References
- 5
- FWCI
- 50.70
- Type
- journal article
- Language
- en
- Open access
- green
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.
