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Record W3097252793 · doi:10.1080/25741292.2020.1841397

Punctuating the equilibrium: an application of policy theory to COVID-19

2020· article· en· W3097252793 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePolicy Design and Practice · 2020
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsQueen's UniversityPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsPunctuated equilibriumExcuseStatus quoCoronavirus disease 2019 (COVID-19)Pandemic2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)EconomicsPolitical scienceLaw and economicsLawVirologyMedicine

Abstract

fetched live from OpenAlex

COVID-19 has taught us that, when inadequately addressed, preexisting policy problems (e.g. weak coordination of healthcare and gaps in income supports) exacerbate the cost of crises (including deaths) and make policy responses more difficult. On a more hopeful note, the pandemic has also revealed that policymakers and bureaucrats, reputed as defenders of the status quo and glacially paced, are capable of moving nimbly when seized with necessity. This manuscript draws on Baumgartner and Jones’ punctuated-equilibrium theory to analyze and demonstrate how policy responses to the pandemic, largely in Canada but also globally, were shaped by preexisting problems (periods of equilibrium). It then raises the question: Will future policy reflect lessons learned through COVID-19, to not only mitigate risks from further crises, but also tackle many other policy challenges? It would seem we can no longer accept the excuse that problems are too complex or time-consuming to tackle.

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 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)0.003
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.849
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.221
GPT teacher head0.520
Teacher spread0.298 · 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