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Record W7094514423

9781000790405.pdf

2022· other· en· W7094514423 on OpenAlexaboutno aff

Bibliographic record

VenueOAPEN (The OAPEN Foundation) · 2022
Typeother
Languageen
FieldMedicine
TopicPharmacological Effects and Toxicity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInjusticeSustainabilityTypologyUrban planningEnvironmental justiceHuman geographySocial sustainabilityUrban sustainability
DOInot available

Abstract

fetched live from OpenAlex

This book uses a unique typology of ten core drivers of injustice to explore and question common assumptions around what urban sustainability means, how it can be implemented, and how it is manifested in or driven by urban interventions that hinge on claims of sustainability. 
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\nAligned with critical environmental justice studies, the book highlights the contradictions of urban sustainability in relation to justice. It argues that urban neighbourhoods cannot be greener, more sustainable and liveable unless their communities are strengthened by the protection of the right to housing, public space, infrastructure and healthy amenities. Linked to the individual drivers, ten short empirical case studies from across Europe and North America provide a systematic analysis of research, policy and practice conducted under urban sustainability agendas in cities such as Barcelona, Glasgow, Athens, Boston and Montréal, and show how social and environmental justice is, or is not, being taken into account. By doing so, the book uncovers the risks of continuing urban sustainability agendas while ignoring, and therefore perpetuating, systemic drivers of inequity and injustice operating within and outside of the city.
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\nAccessibly written for students in urban studies, critical geography and planning, this is a useful and analytical synthesis of issues relating to urban sustainability, environmental and social justice.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.9860.868

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 head0.021
GPT teacher head0.312
Teacher spread0.290 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2022
Admission routes1
Has abstractyes

Explore more

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