Addressing climate change [section 3.1 of The State of New Zealand Report for UN Habitat III]
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
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).1 \nAt 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. \nThe 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. \nThe 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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it