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Record W4413760737 · doi:10.24904/footbridge2025.85

Enhancing a Suicide Barrier – A New Aesthetic Design Challenge

2025· article· en· W4413760737 on OpenAlexaboutno aff
Mark Langridge

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Suicide is a major public health concern that costs hundreds of thousands of lives every year around the world. High landmark bridge crossings have frequently served as a destination for people considering suicide, and as a consequence measures have been taken over the last few decades in many countries to erect suicide prevention barriers on these structures. In many instances, these barriers were designed solely to prevent climbing over. Unfortunately, this approach often ended up conveying a negative “high-security” type appearance that significantly detracts from the above-deck visual aesthetics of the bridge and the everyday pedestrian crossing and viewing experience. Given that bridge life spans are now typically required to be 75-100 years, it is very important that a safety barrier is designed with careful attention to good aesthetics as well as being functional, so that it will achieve an enduring visual quality that is cohesive with other bridge components. Mark Langridge has led the aesthetic and architectural design of many new bridge crossings in important Canadian settings over the past twenty-five years.

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)0.004
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.003

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 head0.052
GPT teacher head0.335
Teacher spread0.282 · 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
Published2025
Admission routes1
Has abstractyes

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