Tensions at the boundary: Rearticulating ‘organic’ plant breeding in the age of gene editing
Bibliographic record
Abstract
A host of technologies is rapidly entering agriculture. These new technologies—particularly gene editing—represent multifaceted shifts beyond “genetic modification” (GM), and are outpacing both public understanding and the capacity of regulatory regimes. This paper employs the case of the organic sectors in Canada and the United States, strongholds of GM resistance, to examine conversations about gene-editing technologies unfolding within the organic community, and elucidate their implications for the sector. We employ the concept of “boundary work” to illuminate how key actors and institutions delineate the concept of organic breeding in the face of emerging technologies. We draw upon semi-structured interviews with organic sector representatives, a review of documents published by organic organizations, and data from participant observation. We find that the organic community is reaffirming and deepening boundaries in response to arguments made by proponents of gene editing. Both internal and external pressures on the sector are facilitating a dampening effect on conversations about the boundaries between gene editing and organic agriculture, as the sector is compelled to present a united voice against the affront of new genetic technologies. The sector is also redrawing existing boundaries, as the advent of gene editing has forced conversations about the compatibility of both new and established breeding methods with organic. The resulting questions about what distinguishes acceptable levels of human intervention in plant genomes are highlighting some differences within the diverse organic community. We also argue that debates about gene editing and organic breeding may be “bounding out” important actors from deliberation processes, and note initial attempts to reckon with this exclusion.
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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 | 0.022 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.038 | 0.100 |
| Scholarly communication | 0.021 | 0.021 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".