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Record W3035855704 · doi:10.1080/21622671.2020.1771022

The COVID-19 pandemic: territorial, political and governance dimensions of the crisis

2020· article· en· W3035855704 on OpenAlexaff
Klaus Dodds, Vanesa Castán Broto, Klaus Detterbeck, Martin Jones, Virginie Mamadouh, Maano Ramutsindela, Monica W. Varsanyi, David Wachsmuth, Chih Yuan Woon

Bibliographic record

VenueTerritory Politics Governance · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsMcGill University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicPolitics2019-20 coronavirus outbreakCorporate governanceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Political sciencePolitical economyBusinessVirologySociologyMedicineLawOutbreak

Abstract

fetched live from OpenAlex

As editors of Territory, Politics, Governance, we want first and foremost to express our solidarity with those affected and impacted directly by the COVID-19 pandemic. While none of us is untouched...

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0070.031
Scholarly communication0.0180.014
Open science0.0010.012
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0080.001

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 head0.063
GPT teacher head0.339
Teacher spread0.277 · 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 designObservational
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

Citations223
Published2020
Admission routes1
Has abstractyes

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