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Record W3040831557 · doi:10.34172/ijhpm.2020.122

Thinking Together, Working Apart: Leveraging a Community of Practice to Facilitate Productive and Meaningful Remote Collaboration

2020· article· en· W3040831557 on OpenAlexafffundabout
Mark Embrett, Rebecca Liu, Katie Aubrecht, Andriy Koval, Jonathan Lai

Bibliographic record

VenueInternational Journal of Health Policy and Management · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsAutism CanadaWomen's College HospitalSt. Francis Xavier University
FundersInstitute of Health Services and Policy Research
KeywordsCoronavirus disease 2019 (COVID-19)PandemicKnowledge managementSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakPublic relationsComputer scienceBusinessPolitical scienceMedicineDisease

Abstract

fetched live from OpenAlex

Considering the coronavirus disease 2019 (COVID-19) pandemic, scholars were encouraged to cease collocated meetings. Many researchers have turned to remote collaboration to continue group-based projects. This paper focuses on the structure, processes, and outcomes that a group of physically distanced, embedded researchers used to collaborate across Canada to produce research outputs prior to the pandemic. The intent of this paper is to provide an overview of mechanisms that can facilitate meaningful and productive remote collaboration using online and digital technologies as a feasible and effective alternative mode of communication for research teams.

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)0.036
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.003
Science and technology studies0.0200.026
Scholarly communication0.0210.015
Open science0.0040.031
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0090.002

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 head0.107
GPT teacher head0.351
Teacher spread0.243 · 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 designQualitative
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

Citations18
Published2020
Admission routes3
Has abstractyes

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Same venueInternational Journal of Health Policy and ManagementSame topicInnovative Approaches in Technology and Social DevelopmentFrench-language works237,207