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Record W7065750815

Embracing Coexistence: urban design strategies for creating wildlife-friendly cities.

2025· other· en· W7065750815 on OpenAlexaboutno aff

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2025
Typeother
Languageen
FieldMaterials Science
TopicElectron and X-Ray Spectroscopy Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsHuman animalUrban designForcing (mathematics)Urban planningClimate changeNon-humanHuman useUrbanization
DOInot available

Abstract

fetched live from OpenAlex

Cities are especially important for human development; it is where people live, build communities, work, learn, and thrive. In cities, human and technological development coincide. But, while building urban and increasingly dense spaces for people’s comfort, other beings are in effect forced to adapt to the ever-growing and changing human habitats. Additionally, major challenges such as climate change resulting in wildfires, flooding, and extreme weather conditions are forcing wild animals and invertebrates to shift closer, if not entirely into human occupied areas. The intense urban densification of the world has affected non-human beings that used to roam freely in those unoccupied areas. Some animals are permanently displaced, while others have successfully adapted to the new human centric environment. Even though wild animals have been able to adapt, cities have not been designed for them, which complicates the way in which they can survive, even as they evolve to co-exist with human urbanites. With an inclusive design approach, this project recognizes both the differences and similarities between human inhabitants and ‘urbanized’ wild animals, as part of having a better understanding to improve the coexistence of species within an urban context. It examines and outlines a range of contemporary initiatives that have been developed and proposed with a focus on designing for animals. The project also gathers information from interviews with experts in wild animal welfare, animal ethics, and sustainable urban planning. In addition to the interviews, data is also collected from an anonymous survey open to people that lives in Toronto. As a result of the research, initial guidelines are proposed to either design new cities or adapt existing urban centres with a more inclusive strategy. These guidelines are organized in three principal areas: infrastructure and planning, government policies and community involvement, and biodiversity conservation and animal welfare. While the project concludes with proposed guidelines, it is understood that it is just an initial stage, and that the journey to have animals, nature, and human beings successfully co-exist in urban centres is an ongoing project in constant adaptation to the rapid and significant changes we are seeing in the environment today.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0050.006
Open science0.0020.010
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.047
GPT teacher head0.323
Teacher spread0.276 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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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