MétaCan
Menu
Back to cohort
Record W2900155794

Access Mode: Inter-personalizing Communication at the workplace [Exhibition Catalogue]

2018· other· en· W2900155794 on OpenAlexaboutno aff

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2018
Typeother
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsnot available
Fundersnot available
KeywordsOpen planInterpersonal communicationPsychologyPlan (archaeology)Emotional intelligenceApplied psychologyWorkforcePublic relationsKnowledge managementSocial psychologyComputer scienceEngineeringPolitical science
DOInot available

Abstract

fetched live from OpenAlex

The collaborative nature of open-plan workplace invites visual, acoustic distractions, digital and social interruptions that inhibits the ability to focus. These distractions can have a direct or indirect impact on individual emotional well-being, work performance, social interactions and in turn organization outcomes. \nTwo leading Tech organizations in Toronto, Canada were approached to study the interpersonal communication within open-plan workplace using mixed methods such as survey, observations, and semi-structured interviews with managers and employees. \n The research explores the question: How can the workplace be better prepared and designed to support the worker of the future with Emotional Intelligence(EI) and Inclusive approaches for performance and effective interpersonal communication? A design prototype is offered as a tool to mitigate the challenges faced by harnessing better interpersonal communication in the open-plan workplace. \nKeywords: Open-Plan Distractions, Social Interruptions, Social Cues, Emotional Well-Being, Interpersonal Communication, Emotional Intelligence, Inclusive Design, Diverse Workforce

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.250
Threshold uncertainty score0.837

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2500.047

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 head0.088
GPT teacher head0.357
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueOCAD University Open Research Repository (OCAD University)Same topicInnovative Human-Technology InteractionFrench-language works237,207