MétaCan
Menu
Back to cohort

Ubiquitous Connectivity & Work-Related Stress

2008· book-chapter· en· W2503592444 on OpenAlexaboutno aff
Jane E. Ramsay, Mario Hair, Karen Renaud

Bibliographic record

VenueIGI Global eBooks · 2008
Typebook-chapter
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsPaceStressorPerceptionWork (physics)Everyday lifePsychologyQuarter (Canadian coin)Social psychologyEngineeringGeographyPolitical science

Abstract

fetched live from OpenAlex

The way humans interact with one another in the 21st Century has been markedly influenced by the integration of a number of different communication technologies into everyday life, and the pace of communication has increased hugely over the past twenty-five years. This chapter introduces work by the authors that considers the ways one communication-based technology, namely e-mail, has impacted workers’ “thinking time”, and become both a “workplace stressor” and an indispensable communications tool. Our research involved both a longitudinal exploration (three months) of the daily e-mail interactions of a number of workers, and a survey of individuals’ perceptions of how e-mail influences their communication behaviour in general, and their work-related communication in particular. Initial findings, in the form of individual differences, are reported here. The findings are presented in relation to the way workplace stressors have changed over the past quarter century.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.008

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 head0.176
GPT teacher head0.373
Teacher spread0.197 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueIGI Global eBooksSame topicPersonal Information Management and User BehaviorFrench-language works237,207