Citizens as consumers: styles of reasoning about agricultural biotechnologies and publics
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
In research and policy there is a dominant style of reasoning about the contribution agricultural biotechnologies can make to resolving major global challenges. In this reasoning, consumer scepticism is a major hindrance to deploying biotechnology and there is a significant focus on understanding consumer opinion in order to manipulate it. Analysing the historical role given to publics in public opinion research, and within technology research and policy, demonstrates that the framing of publics is largley shaped by economics. A review of academic publications on agricultural biotechnology and publics between 1995 and 2021 reveals some of the core tenets of this style of reasoning. The dominant framing of publics as individual consumers confines attention to concerns with end products on supermarket shelves. Theories and methods are focused on understanding individual perceptions, and fixed response questions reify the expert/public divide. This obscures broader public concerns with agricultural biotechnologies, such as issues of social justice or governance of uncertainty. A broader framing of different publics and their opinions of technology development and deployment would improve understanding of the issues that concern people as citizens, and enable more meaningful public engagement with agricultural biotechnologies.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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