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Record W2552751958

Addressing climate change [section 3.1 of The State of New Zealand Report for UN Habitat III]

2016· article· en· W2552751958 on OpenAlexaboutno aff
Hugh Byrd

Bibliographic record

VenueLincoln Repository (University of Lincoln) · 2016
Typearticle
Languageen
FieldDecision Sciences
Topicdemographic modeling and climate adaptation
Canadian institutionsnot available
Fundersnot available
KeywordsAotearoaPopulationGeographyUrbanizationPovertyPolitical scienceEconomic growthEnvironmental planningSociology
DOInot available

Abstract

fetched live from OpenAlex

Habitat III is the third bi-decennial United Nations conference on Housing and Sustainable Urban Development to take place in Quito Ecuador, 17- 20 October 2016. The UN General Assembly, adopted a resolution that ‘the objectives of the Conference are to secure renewed political commitment for sustainable urban development, assess accomplishments to date, address poverty and identify and address new and emerging challenges’ (Resolution 67/216).1At the time of the first Habitat Conference in Vancouver in 1976, the population of New Zealand was 3.1 million, of whom over 2.5 million were living in urban areas.2 Today the population is 4.4 million and due to increase to 5.5million by 2038, if current projections are correct. New Zealand is not alone. As the world population has been increasing, so too has the percentage of the population living in urban areas. The phenomenon is global. The challenge is to ensure that the urbanisation taking place is sustainable.The State of New Zealand report was produced in the run up to Habitat III in October 2016. The aim of this report is to stimulate debate in Aotearoa New Zealand, amongst researchers and academics as well as the wider community, on our urban issues and the future direction we need to take. The report also aims to initiate discussions about the role of Universities in achieving the new urban agenda and the way in which professionals need to be educated and trained.The report has been finalised to coincide with the third preparatory committee meeting (Prepcom3) in Surabaya, Indonesia between 25-27th July 2016 at which the revised zero draft of the New Urban Agenda was discussed

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.602
Threshold uncertainty score0.800

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0030.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0260.012

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 head0.120
GPT teacher head0.318
Teacher spread0.198 · 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
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
Published2016
Admission routes1
Has abstractyes

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