MétaCan
Menu
Back to cohort
Record W2342907215

Driving in the wrong lane: towards a longer life-span of cars

2015· book-chapter· en· W2342907215 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNottingham Trent University's Institutional Repository (Nottingham Trent Repository) · 2015
Typebook-chapter
Languageen
FieldEngineering
TopicTechnology Assessment and Management
Canadian institutionsnot available
FundersResearch Councils UKTrent UniversityNottingham Trent University
KeywordsLongevityContext (archaeology)Product (mathematics)Automotive industryLife spanProduct designEngineeringProduct lifecycleOrder (exchange)Sustainable consumptionNew product developmentRisk analysis (engineering)MarketingBusinessProduction (economics)EconomicsGeography
DOInot available

Abstract

fetched live from OpenAlex

Within the context of product longevity, one especially impactful and ubiquitous product demands further research: the car. Car longevity has been addressed in the context of product life extension and product lifetime optimisation but there have been a few studies on car longevity in the context of business and none specifically from an industrial design context. This paper presents initial findings from preliminary interviews with key industry representatives such as car designers and engineers. It discusses the barriers to and opportunities for designing a car with a longer life-span. This and further data will later be analysed in order to produce a design framework to inform car
\ndesigners on life-span and usage optimization through design. Strategies such as increased longevity or use-intensity can potentially reduce the throughput - and thereafter the consumption - of cars. Such a shift in the automotive sector would support the transition from a linear economy to a more sustainable one. The initial findings, however, suggest that a longer life car is not an uncompromised solution and important concessions would have to be made in order to make this an acceptable
\nproduct.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.201
Teacher spread0.185 · 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