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Record W4281485703 · doi:10.1186/s12544-022-00547-0

Implications of COVID-19 for future travel behaviour in the rural periphery

2022· article· en· W4281485703 on OpenAlexfundno aff
John D. Nelson, Brian Caulfield

Bibliographic record

VenueEuropean Transport Research Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
FundersTransport Canada
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Transport engineeringEngineeringForensic engineeringVirologyMedicineOutbreak

Abstract

fetched live from OpenAlex

Background: The design, management and operation of transport systems is a complex activity and this has only been exacerbated since the onset of the COVID-19 pandemic. Concern has been raised over the likelihood of the public transport sector surviving in some locations given the significant drops in patronage; this is especially so in rural environments where the existing provision was already limited. Furthermore, within the growing literature on the impact of COVID-19 on travel behaviour most of the focus is on urban areas with little documented experience of how rural travel behaviour has been impacted. Purpose: This paper investigates the impact of COVID-19 on the transport sector and travel behaviour in the rural periphery. Methods: Drawing on the work of the International Transport Forum (ITF) Working Group on Innovative Mobility for the Periphery, augmented by additional evidence and findings from the literature, this paper addresses three specific questions: Firstly, how COVID-19 has affected rural mobility. Secondly, how we can plan for sustainable rural transport solutions in the post-COVID world. Thirdly, the longer-term impacts of COVID-19 with implications for mobility. Results: There will be substantial impacts from COVID-19 on rural societies and while the short-term impacts have been negative, in the longer-term there may be opportunity for changed mobility behaviours (including in response to modified work and activity patterns). Evidence suggests that it would seem likely that there are opportunities to foster new rural mobility solutions to support sustainable mobility (including Mobility-as-a-Service) and counter the traditionally fragmented transport base; this will be important as we learn to live with COVID-19. Conclusions: While recognising the impact of changing funding priorities and the possible shift in economic activity as a result of the pandemic we conclude with suggestions for future rural transport policy.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.171
GPT teacher head0.447
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

Citations25
Published2022
Admission routes1
Has abstractyes

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