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Record W3134546507 · doi:10.1017/s174413312100013x

Going hard and early: Aotearoa New Zealand's response to Covid-19

2021· article· en· W3134546507 on OpenAlexaff
Jacqueline Cumming

Bibliographic record

VenueHealth Economics Policy and Law · 2021
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsInstitute of Health Services and Policy Research
Fundersnot available
KeywordsAotearoaSocial distanceCoronavirus disease 2019 (COVID-19)PandemicLimitingPrime ministerPersonal protective equipment2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Political scienceContact tracingPublic relationsMedicinePoliticsLawVirologyEngineering

Abstract

fetched live from OpenAlex

Aotearoa New Zealand went 'hard' and 'early' in its response to COVID-19 and has been highly successful in limiting the spread and impact of the virus. The response has ramped up over time, and has included various levels of: border control; advice on hygiene, physical distancing and mask wearing; advice to remain at home if unwell; and testing and tracing. A four-level Alert Level framework has guided key actions at different levels of risk. Strong leadership from the Prime Minister, Minister of Finance, and Director-General of Health and high levels of community co-operation have supported the response. The country is most vulnerable at its borders, where arrangements have been of concern; advice on testing and the wearing of masks has changed over time; while the use and distribution of personal protective equipment has also been of concern. The country overall was not well prepared for a pandemic, but policy-making has been nimble. Key challenges for 2021 include swiftly rolling out a vaccine, catching up on delayed health care, and deciding how and when the border can reopen. The economic, and associated social, challenges will last many years.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.604
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.259
GPT teacher head0.453
Teacher spread0.194 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations57
Published2021
Admission routes1
Has abstractyes

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