MétaCan
Menu
Back to cohort
Record W4239312656 · doi:10.32920/ryerson.14655936.v1

Continuity after catastrophe: temporary commercial developments for post-disaster recovery

2021· preprint· en· W4239312656 on OpenAlexaff
Andrew Gavel

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDisaster recoveryNatural disasterBusinessContainer (type theory)Environmental planningOperations managementGeographyEngineeringPolitical science

Abstract

fetched live from OpenAlex

This major research paper explores opportunities to support small businesses after natural disasters through the creation of temporary commercial developments. The Re:START Christchurch shipping container mall is selected as a case study for further examination into the built-form and urban design characteristics that best support recovery needs. The findings of this paper indicate that Re:START Christchurch not only does a good job of addressing the post-disaster needs of businesses, but also serves to strengthen the identity and community of the recovering city. Best practices and recommendations are extracted from this example to be considered for the Pacific Northwest and other cities recovering from future natural disasters. Keywords: disaster recovery, temporary development, small businesses, urban design

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.024
GPT teacher head0.305
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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicDisaster Management and ResilienceFrench-language works237,207