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Record W4411857145 · doi:10.1016/j.orgdyn.2025.101172

Hybrid and remote team chartering: Creating clarity in an increasingly virtual world

2025· article· en· W4411857145 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOrganizational Dynamics · 2025
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsMount Royal UniversityUniversity of WaterlooUniversity of Calgary
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsCLARITYBusiness

Abstract

fetched live from OpenAlex

Team chartering is the process of creating an agreement that outlines how team members will work together. Whereas all teams can benefit from chartering, hybrid and remote teams might find it particularly important due to challenges in building trust, coordinating workflows, and maintaining consistent communication. However, although chartering can be beneficial for hybrid and remote teams, practitioners may not know how to get started, what to include, and how to ensure it impacts the team positively. This paper offers a set of practical guidelines and facilitation strategies to lead effective chartering sessions for hybrid and remote teams. It includes a charter template, recommended practices, and implementation guidelines. This work was informed by research in the social-psychological and organizational literature, the authors’ expertise and experiences in working with hundreds of teams to improve their functioning, and a program of research utilizing the charter template with a variety of corporate teams. Teams going through the chartering process can expect that it will streamline their teamwork practices and address challenges of hybrid and remote teaming.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.007
GPT teacher head0.273
Teacher spread0.265 · 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