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Record W745831610

A Spoonful of Trust Helps the Nanotech Go Down

2004· article· en· W745831610 on OpenAlexaboutno aff
Bryn Williams–Jones

Bibliographic record

VenueDigitalGeorgetown (Georgetown University Library) · 2004
Typearticle
Languageen
FieldEngineering
TopicNanotechnology research and applications
Canadian institutionsnot available
Fundersnot available
KeywordsVisionDystopiaGovernment (linguistics)Public trustEnablingPublic relationsPolitical scienceBusinessSociologyLawMedicine
DOInot available

Abstract

fetched live from OpenAlex

Introduction Utopian and dystopian visions of nanotechnology are prominent in both the public press and academic literature. Proponents argue that nanotechnologies will help clean the environment, produce cheap energy and eliminate poverty, (1) while opponents respond that nanotechnologies will undermine local economies, raise serious health and safety issues, and possibly even destroy the environment. (2) It would be easy to reject out of hand these visions as extreme and irrelevant, because they do not represent the current or likely future states of the technology. However, this move side-steps the question of why these extreme visions arise, and more importantly, the problems that such polarized discussions create for public trust in government and science. As should be clear from recent experiences in Europe with genetically modified (GM) foods, it is no longer sufficient for governments, scientists and industry to deploy a technology that experts have deemed safe and effective--the general public must also buy the new technology if it is to be adopted. But this buy-in and public trust can be significantly undermined by the hyping of new technologies. In this paper, I argue that if governments, academic scientists and industry wish to effectively develop the potential of nanoscience and nanotechnologies, they must be cognizant of the dangers of over-hyping research and losing public trust. Hype Hype is arguably an important part of the opening phases in the development of a new technology, because it facilitates the creation of new networks of relations, helps in the acquisition of necessary resources (human, financial, technical), and permits the development of a popular consciousness about how the new technology will replace old, less effective ways of doing things. (3) By projecting an image of where a technology will lead, developers create a possible future that is fundamental to producing the incentives and obligations that will be necessary to mobilise the necessary resources for a particular aspiration to be realised. (4) To project the desired future image (and attract public or private research funding), scientists and universities will often, alongside more objective academic articles, make press releases and conduct media interviews that highlight the benefits and novelty of their research. The media in turn respond to broad public interest in science and technology by reporting on new discoveries. But while this reporting is usually factually accurate, it tends to be uncritical of scientific claims, focusing on the positive or novel aspects of the products of research while neglecting the limitations. (5) Although hype can be a very effective means of achieving these near term objectives, it can also be counterproductive in the long run. If we look at the case of GM crops and foods, for example, we see a set of technologies that were promised to be revolutionary (but safe), and that would quickly lead to enormous social, economic and environmental benefits. Governments (and industry) in the United States, Argentina, Canada and China have invested significant public monies in GM technologies (and implemented supportive agricultural and intellectual property rules) in the hope that these technologies will provide a competitive advantage for their large and heavily subsidized agricultural sectors. However, as with many other biotechnologies, such as gene therapy or pharmacogenetics, the promises have largely proven premature, the hype unsubstantiated, and for the most part the general public has yet to see any tangible benefits. (6) It should not then be surprising that many people are becoming sceptical of (and militant about challenging) the positive claims made by governments and industry about the safety and utility of GM foods and other biotechnologies. A culture of hype can also lead to weaker market conditions and skittish investors. As we saw in the late 1990s, the inability of most small biotechnology companies to make good on promises and translate intellectual property into marketable products led many venture capitalists to back away from this sector. …

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.074
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.037
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.074
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0110.021
Scholarly communication0.0290.034
Open science0.0020.017
Research integrity0.0150.017
Insufficient payload (model declined to judge)0.0370.019

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.

Opus teacher head0.004
GPT teacher head0.157
Teacher spread0.153 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations9
Published2004
Admission routes1
Has abstractyes

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