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Record W3128468683

Post-disaster Urbanism — with Mary Rowe

2020· article· en· W3128468683 on OpenAlexaboutno aff
Mary P. Rowe, Am Johal, Fiorella Pinillos, Melissa Roach, Paige Smith, Kathy Feng, Alex Abahmed

Bibliographic record

VenueSummit (Simon Fraser University) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsnot available
Fundersnot available
KeywordsROWEUrbanismGeographyArchaeologyArchitectureBusiness
DOInot available

Abstract

fetched live from OpenAlex

Mary is a leading urban advocate and civil society leader who has worked in cities across Canada and the United States. Mary comes to the Canadian Urban Institute with several years of experience as an urban advocate and community leader, including serving as Executive Vice President of the Municipal Art Society of New York (MASNYC), one of America’s oldest civic advocacy organizations focused on the built environment. A mid-career fellowship with the US-based blue moon fund led her to New Orleans where she worked with national philanthropy, governments and local communities to support rebuilding after Hurricane Katrina. Prior, Mary was President of the Canadian platform Ideas That Matter, a convening and publishing program based on the work of renowned urbanist Jane Jacobs.\n\nMary has been a frequent contributor to national and international city-building programs, including UN Habitat and the World Urban Forum. She brings an extensive international network of practitioners from government, industry, community activism, and the city-building professions to strengthen CUI under her leadership.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.002
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0220.008

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 head0.207
Teacher spread0.190 · 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
Published2020
Admission routes1
Has abstractyes

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