Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,317

The DOI matches its Crossref record.

A Basis for Scaling Qualitative Data

Guttman, Louis·1944·American Sociological Review

Abstract

IN A GREAT deal of research in the social and psychological sciences, interest lies in certain large classes of qualitative observations. For example, research in marriage is concerned with a class of qualitative behavior called marital adjustment, which includes an indefinitely large number of interactions between husband and wife. Public opinion research is concerned with large classes of behavior like expressions of opinion by Americans about the fighting ability of the British. Educational psychology deals with large classes of behavior like achievement tests. It is often desired in such areas to be able to summarize data by saying, for example, that one marital couple is better adjusted than another marital couple, or that one person has a better opinion of the British than has another person, or that one student has a greater knowledge of arithmetic than has another student. There has been considerable discussion concerning the utility of such orderings of persons. It is not our intention in this paper to review such discussions, but instead to present a rather new approach to the problem which seems to afford an adequate basis for quantifying qualitative data. This approach has been used successfully for the past year or so in investigating morale and other problems in the United States Army by the Research Branch of the Morale Services Division of the Army Service Forces. While this approach to quantification leads to some interesting mathematics, no knowledge of this mathematics is required in actually analyzing data. Simple routines have been established which require no knowledge of statistics, which take less time than the various manipulations now used by various

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2307/2086306

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.

A few free checks a day · papers already verified open instantly · results are public

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

See all 1,317

Metadata

Authors
Guttman, L.
Venue
American Sociological Review
Published
1944-04
Volume
9
Issue
2
Pages
139
ISSN
0003-1224 (ISSN-L)
OpenAlex
W2332834163
Cited by
1,317
References
0
FWCI
9.49
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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A Basis for Scaling Qualitative Data. https://app.cochat.ai/papers/10.2307/2086306
The paper
Guttman, L. (1944). A Basis for Scaling Qualitative Data. American Sociological Review. https://doi.org/10.2307/2086306

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.