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Record W4403196115 · doi:10.3311/ccc2024-067

Prolonging The Life-Time of New Deal Bridges

2024· article· en· W4403196115 on OpenAlexaff
Christian Koch

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Bridges constructed during the depression of the 1930ties are now at the end of their lifetime. Similar to Roosevelts “new deal” from this period, leading to creation of employment and wealth, EU is now proposing a “new green deal” to reach climate neutrality. But how can the transformation of these bridges be done to support such an agenda? The framework of understanding proposes uses a broader sustainable transition framework integrating megaproject management concepts, circularity and science technology and society (STS) concepts. Circularity in civil engineering and mega projects are still somewhat underconceptualised. Here the Institution of Civil Engineers (ICE UK)-s concepts are used. To this is added the notion of hierarchy of reuses, taken from EU concept of “hierarchy of waste”. The contribution present analysis a specific case of a Danish bridge made in the 1930ties, the 3200 meters long Storstrømsbro. We analyse how the actual sustainable transition work is carried out at the old and new bridge. Building further on a broader portfolio of Danish bridges built during the same period, we propose a more sustainable transition. So far consultants have proposed to use the Building Research Environment (BRE) standard for civil infrastructure for the Storstrømsbro but where this provide a processual model, there is little guidance as to which solutions is the more sustainable for demolition. Some bridges clearly faces to be demolished, some are transformed into secondary crossings, but potentially they could be renovated to serve society with a sustainable circular solution. New Green Deal is part of the EU plan for mitigating climate change. This includes circularity. However, changing existing infrastructure into circular artefacts might prove difficult and run into technological momentum.

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)0.002
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.017
GPT teacher head0.289
Teacher spread0.272 · 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
GenreEmpirical

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

Citations0
Published2024
Admission routes1
Has abstractyes

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