The three main monotheistic religions and gm food technology: an overview of perspectives
Bibliographic record
Abstract
BACKGROUND: Public acceptance of genetically modified crops is partly rooted in religious views. However, the views of different religions and their potential influence on consumers' decisions have not been systematically examined and summarized in a brief overview. We review the positions of the Judaism, Islam and Christianity - the three major monotheistic religions to which more than 55% of humanity adheres to - on the controversies aroused by GM technology. DISCUSSION: The article establishes that there is no overarching consensus within the three religions. Overall, however, it appears that mainstream theology in all three religions increasingly tends towards acceptance of GM technology per se, on performing GM research, and on consumption of GM foods. These more liberal approaches, however, are predicated on there being rigorous scientific, ethical and regulatory scrutiny of research and development of such products, and that these products are properly labeled. SUMMARY: We conclude that there are several other interests competing with the influence exerted on consumers by religion. These include the media, environmental activists, scientists and the food industry, all of which function as sources of information and shapers of perception for consumers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".