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Record W2159339345 · doi:10.5465/amj.2013.0991

Seeing the Forest for the Trees: Exploratory Learning, Mobile Technology, and Knowledge Workers’ Role Integration Behaviors

2014· article· en· W2159339345 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

VenueAcademy of Management Journal · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsMcGill UniversityYork University
Fundersnot available
KeywordsKnowledge managementPsychologyOrganizational behaviorExploratory researchBusinessSociologyPublic relationsMarketingSocial psychologyComputer sciencePolitical scienceSocial science

Abstract

fetched live from OpenAlex

Role integration is the new workplace reality for many employees. The prevalence of mobile technologies (e.g., laptops, smartphones, tablets) that are increasingly wearable and nearly always “on” makes it difficult to keep role boundaries separate and distinct. We draw upon boundary theory and construal level theory to hypothesize that role integration behaviors shift people from thinking concretely to thinking more abstractly about their work. The results of an archival study of Enron executives’ emails, two experiments, and a multi-wave field study of knowledge workers provide evidence of positive associations between role integration behaviors, higher construal level, and more exploratory learning activities.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.025
GPT teacher head0.313
Teacher spread0.288 · 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