MétaCan
Menu
Back to cohort
Record W2022350552 · doi:10.1111/1539-6924.00256

Life Cycle Impact Assessment: A Challenge for Risk Analysts

2002· article· en· W2022350552 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRisk Analysis · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRisk analysis (engineering)Life-cycle assessmentRisk assessmentBusinessEnvironmental economicsComputer scienceProduction (economics)EconomicsComputer security

Abstract

fetched live from OpenAlex

Modern technology, together with an advanced economy, can provide a good or service in myriad ways, giving us choices on what to produce and how to produce it. To make those choices more intelligently, society needs to know not only the market price of each alternative, but the associated health and environmental consequences. A fair comparison requires evaluating the consequences across the whole "life cycle"--from the extraction of raw materials and processing to manufacture/construction, use, and end-of-life--of each alternative. Focusing on only one stage (e.g., manufacture) of the life cycle is often misleading. Unfortunately, analysts and researchers still have only rudimentary tools to quantify the materials and energy inputs and the resulting damage to health and the environment. Life cycle assessment (LCA) provides an overall framework for identifying and evaluating these implications. Since the 1960s, considerable progress has been made in developing methods for LCA, especially in characterizing, qualitatively and quantitatively, environmental discharges. However, few of these analyses have attempted to assess the quantitative impact on the environment and health of material inputs and environmental discharges Risk analysis and LCA are connected closely. While risk analysis has characterized and quantified the health risks of exposure to a toxicant, the policy implications have not been clear. Inferring that an occupational or public health exposure carries a nontrivial risk is only the first step in formulating a policy response. A broader framework, including LCA, is needed to see which response is likely to lower the risk without creating high risks elsewhere. Even more important, LCA has floundered at the stage of translating an inventory of environmental discharges into estimates of impact on health and the environment. Without the impact analysis, policymakers must revert to some simple rule, such as that all discharges, regardless of which chemical, which medium, and where they are discharged, are equally toxic. Thus, risk analysts should seek LCA guidance in translating a risk analysis into policy conclusions or even advice to those at risk. LCA needs the help of RA to go beyond simplistic assumptions about the implications of a discharge inventory. We demonstrate the need and rationale for LCA, present a brief history of LCA, present examples of the application of this tool, note the limitations of LCA models, and present several methods for incorporating risk assessment into LCA. However, we warn the reader not to expect too much. A comprehensive comparison of the health and environmental implications of alternatives is beyond the state of the art. LCA is currently not able to provide risk analysts with detailed information on the chemical form and location of the environmental discharges that would allow detailed estimation of the risks to individuals due to toxicants. For example, a challenge for risk analysts is to estimate health and other risks where the location and chemical speciation are not characterized precisely. Providing valuable information to decisionmakers requires advances in both LCA and risk analysis. These two disciplines should be closely linked, since each has much to contribute to the other.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.000

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.

Opus teacher head0.010
GPT teacher head0.280
Teacher spread0.270 · 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