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Record W1515783637 · doi:10.1111/1467-8551.12027

Mobile Technology and Boundary Permeability

2013· article· en· W1515783637 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.

Bibliographic record

VenueBritish Journal of Management · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsWestern UniversityCarleton University
Fundersnot available
KeywordsSensemakingAttributionBoundary (topology)Knowledge managementWork (physics)Mobile deviceControl (management)Computer sciencePsychologySociologyMarketingBusinessSocial psychologyEngineeringMathematicsWorld Wide Web

Abstract

fetched live from OpenAlex

An extensive review of the literature reveals a lack of insight into why some employees and their families benefit from the adoption of mobile technology while others do not. The paper summarizes the authors' efforts to answer this question. The authors undertook a longitudinal case study of the adoption and use of a B lack B erry S martphone by 25 professional knowledge workers. Four theoretical lenses were used to help with the data analysis process: boundary theory, the social constructivist view of technology, sensemaking and attribution theory. Analysis of the Time 2 data identified three groups. Segmentors (n = 4) did not use their smartphones outside work hours. Integrators (n = 8), used their smartphones to connect to both work and family anywhere, but not any time (temporally separated work and family roles). Struggling segmentors (n = 13) felt pressured by their organization to use their device 24/7 and did so. The analysis indicates that the relationship between the use of mobile technology and successful boundary management depends on the development of a strategy to manage the device prior to adoption, the ability to change one's strategy to respond to concerns at home, and self‐control.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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