MétaCan
Menu
Back to cohort
Record W4384930421 · doi:10.1080/19427867.2023.2237269

What have we learned about long-term structural change brought about by COVID-19 and working from home?

2023· article· en· W4384930421 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTransportation Letters · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicQuarter (Canadian coin)2019-20 coronavirus outbreakTerm (time)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Work (physics)PopulationPolitical scienceEconomic growthDevelopment economicsPublic relationsPsychologySociologyHistoryMedicineEconomicsEngineeringDemographyVirology

Abstract

fetched live from OpenAlex

March 2020 will forever be etched in our minds as the beginning of the most concerning health pandemic faced by all generations of the living population. Two-and-three quarter years on, we are starting to see signs for what the future might evolve into through structural change brought about by many events, and no more so than the burgeoning growth in working from home (WFH). WFH is no longer associated with negative stigma, and along with remote working more generally, has become recognised across most sectors of society as a way of work that has benefits for many and is to some extent here to stay. We draw on the research undertaken since March 2020 to summarise the evidence that we use to speculate on what are likely to be the big changes in the land transport sector that would not have been considered, at least to the same extent, pre-COVID-19.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.087
GPT teacher head0.296
Teacher spread0.209 · 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