Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 219

The DOI matches its Crossref record.

Who Does the Public Trust? The Case of Genetically Modified Food in the United States

Lang, John T., Hallman, William K.·2005·Risk Analysis

Abstract

Trust is important for the perception of many types of risk, including those relating to genetically modified (GM) food. Who the public trusts in any given circumstance, however, is not well understood. In this study of public trust regarding GM food, an exploratory factor analysis with Promax rotation reveals public classification of three common institutional types—evaluators, watchdogs, and merchants. The structure of relationships among these stakeholders can act to enable or constrain public support for this new technology. Evaluators—scientists, universities, and medical professionals—are the most trusted. Watchdogs—consumer advocacy organizations, environmental organizations, and media sources—are moderately trusted. Merchants—grocers and grocery stores, industry, and farmers—are least trusted. While the federal government is seen as closest to being an evaluator, it is not highly correlated with any of the factors. The lack of trust in the organizations with the greatest resources and responsibilities for ensuring the safety of GM food should be seen as an important obstacle to the adoption of the technology.

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 · 10.1111/j.1539-6924.2005.00668.x

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 219

Metadata

Authors
Lang, J. T., & Hallman, W. K.
Venue
Risk Analysis
Publisher
Wiley
Published
2005-10
Volume
25
Issue
5
Pages
1241-1252
ISSN
  • 0272-4332 (ISSN-L)
  • 1539-6924
OpenAlex
W2171718655
Cited by
219
References
0
FWCI
36.31
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: Who Does the Public Trust? The Case of Genetically Modified Food in the United States. https://app.cochat.ai/papers/10.1111/j.1539-6924.2005.00668.x
The paper
Lang, J. T., & Hallman, W. K. (2005). Who Does the Public Trust? The Case of Genetically Modified Food in the United States. Risk Analysis. https://doi.org/10.1111/j.1539-6924.2005.00668.x

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.