Bridging the Divide: An Interdisciplinary Analysis of Trust in Science

For several reasons, trust in science in recent years has eroded, throwing serious doubts on once-reliable scientific resources. Although multiple scientific disciplines try to explain the causes and consequences of this worrying decline, we have only scant knowledge about these disciplines’ interconnected arguments. Focusing on this niche, this study aims to bridge the literature from diverse academic disciplines and identify dominant themes by utilising a cutting-edge methodology. This attempt is crucial since we need a comprehensive understanding of the complex factors influencing public trust in science, allowing us to approach the problem from multiple angles and enabling the crafting of evidence-based policies that better resonate with the public and are more likely to be effective in restoring trust. Hence, this study contributes to the existing literature both substantially and methodologically. Substantially, we show that there are dominant recurring research themes across the disciplines, such as science communication, compliance with scientific advice, and public engagement. Methodologically, we contend that identifying these vital crosscutting themes can only be possible by combining state-of-the-art computational techniques with conventional qualitative content analysis.

Authors

Institutions

Publication Details

Journal
SAGE Open
Published
2025-01-01
DOI
https://doi.org/10.1177/21582440251352376
Citations
1
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
5.34

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bridging the Divide: An Interdisciplinary Analysis of Trust in Science

Gökçe Zeybek Kabakçı, Umut Yener Kara, Emre Toros, Gökçe Baydar Çavdar
1 citations
SAGE Open
Computational and Text Analysis Methods
5.34
article

Bridging the Divide: An Interdisciplinary Analysis of Trust in Science

Gökçe Zeybek Kabakçı, Umut Yener Kara, Emre Toros, Gökçe Baydar Çavdar
article en
1 citations

Abstract

For several reasons, trust in science in recent years has eroded, throwing serious doubts on once-reliable scientific resources. Although multiple scientific disciplines try to explain the causes and consequences of this worrying decline, we have only scant knowledge about these disciplines’ interconnected arguments. Focusing on this niche, this study aims to bridge the literature from diverse academic disciplines and identify dominant themes by utilising a cutting-edge methodology. This attempt is crucial since we need a comprehensive understanding of the complex factors influencing public trust in science, allowing us to approach the problem from multiple angles and enabling the crafting of evidence-based policies that better resonate with the public and are more likely to be effective in restoring trust. Hence, this study contributes to the existing literature both substantially and methodologically. Substantially, we show that there are dominant recurring research themes across the disciplines, such as science communication, compliance with scientific advice, and public engagement. Methodologically, we contend that identifying these vital crosscutting themes can only be possible by combining state-of-the-art computational techniques with conventional qualitative content analysis.

SAGE OpenVol. 15(3)
Bilkent University (TR), WZB Berlin Social Science Center (DE), Hacettepe University (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Openalex Percentile: Top 4%
Computational and Text Analysis Methods
5.34
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.