Applying a precautionary risk management strategy for regulation of nanotechnology
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
Nanotechnology promises a multiplicity of benefits to society. At the same time it has become a focus of debate regarding potential health and other associated risks. Rejection of new nanotechnology innovations could result in loss of trust in regulators, a phenomenon observed previously with nuclear and genetically altered food crop technologies. Due to this uncertainty a precautionary approach is warranted. The anticipated four stages of nanotechnology development, from passive to more active forms, are arrayed against existing risk management strategies of a precautionary nature. The overlay suggests that precaution is appropriate for all stages of nanotechnology development. Other effects from innovation, such as socio-economic inequity, disruptive impact on labour markets, alteration of global trade and unintended health and environmental impacts, can also be minimised by applying a precautionary approach. The use of a precautionary approach can provide protection to developers of nanotechnology, to individuals and to the environment.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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