Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 432

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Unrewarding Work, Coworker Support, and Job Satisfaction: A Test of the Buffering Hypothesis

DUCHARME, LORI J., MARTIN, JACK K.·2000·Work and Occupations

Abstract

Beneficial effects of social support in the workplace have received only limited attention from sociologists. Workgroup interactions, especially social support received from coworkers, may significantly contribute to job satisfaction. This article assesses the effects of coworker support on job satisfaction, paying particular attention to the nature and influence of instrumental coworker support both relative to and in conjunction with affective coworker support. The authors expect that both affective and instrumental social support will exert significant and independent effects on these outcomes and that instrumental support will buffer the effects of nonrewarding work on job satisfaction. These hypotheses are tested in a series of ordinary least squares regression models. Data are drawn from a nationally representative sample of 2,505 full-time employees. Study findings are consistent with a main effects model of workplace social support. Suggestions for the absence of buffering effects, implications for industrial policy, and future research efforts are offered.

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 · 10.1177/0730888400027002005

Cites

4 of 4 references verified0 citation errors · 0 not checkable

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

Cites

Show all 4 references

Cited by

See all 432

Metadata

Authors
DUCHARME, L. J., & MARTIN, J. K.
Venue
Work and Occupations
Published
2000-05
Volume
27
Issue
2
Pages
223-243
ISSN
  • 0093-9285 (ISSN-L)
  • 0730-8884
  • 1552-8464
OpenAlex
W2066014483
Cited by
432
References
4
FWCI
8.13
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: Unrewarding Work, Coworker Support, and Job Satisfaction: A Test of the Buffering Hypothesis. https://app.cochat.ai/papers/10.1177/0730888400027002005
The paper
DUCHARME, L. J., & MARTIN, J. K. (2000). Unrewarding Work, Coworker Support, and Job Satisfaction: A Test of the Buffering Hypothesis. Work and Occupations. https://doi.org/10.1177/0730888400027002005

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.