The Power of Stories: Narratives and Information Framing Effects in Science Communication
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article explores information framing effects by comparing the effectiveness of using logical‐scientific versus narrative information to communicate with consumers about a new biotechnology application (gene editing). Using data from an online survey of 804 Canadian adults, a discrete choice experiment elicits preferences for diverse novel food attributes and technologies, with respondents randomly assigned to different information conditions. We construct a logical‐scientific information condition, written in a scientific style using the passive voice with generalized and impersonal language and attributed to either a government agency or a scientific organization. In contrast, we frame the narrative‐style information condition as a story, using a lively and vivid personal style, and attributed to either a science journalist or a consumer blogger. Data are analyzed using multinomial logit and random parameters logit models. We find that the information format (logical‐scientific vs. narrative) matters: narratives help reduce negative perceptions regarding agricultural and food technologies. We also examine factors that predispose consumers to seek logical‐scientific versus narrative information sources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it