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Record W2133425163 · doi:10.1002/meet.14505001089

Challenges of information system use by knowledge workers: The email productivity paradox

2013· article· en· W2133425163 on OpenAlexaff
Inge Alberts

Bibliographic record

VenueProceedings of the American Society for Information Science and Technology · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsWilfrid Laurier UniversityUniversity of Ottawa
Fundersnot available
KeywordsProductivityKnowledge managementComputer scienceKnowledge workerWork (physics)Cloud computingInformation technologyKey (lock)Forcing (mathematics)Perspective (graphical)Social mediaInformation systemData scienceEngineeringWorld Wide WebComputer security

Abstract

fetched live from OpenAlex

Abstract With the growing importance of social media, cloud computing and mobile device interactions, the digital work environment is being perpetually transformed while forcing users to adapt to the emerging technologies. In this volatile environment, research leading to innovative approaches to better support the information practices of knowledge workers is acquiring a critical importance. Aiming to improve the technological and organizational policy‐making decisions for the implementation of new information systems, this paper examines the current challenges of 34 knowldege workers using information systems to perform their daily tasks. A qualitative research approch entailing the use of semi‐directed interviews and diary journals is followed to this end. The outcomes of this research are both theoretical and practical. This research provides a critical insight into the key challenges facing knowledge workers in the digital work environment. From a purely practical perspective, this study helps uncover the needs and expectations of knowledge workers as they use email and other technologies to achieve their work tasks. In light of this study, the technological and organizational policy‐making decisions for the implementation of new information systems must ensure that email as a tool drives true productivity and avoids the productivity paradox.

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 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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.688
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.003
Scholarly communication0.0000.013
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 head0.097
GPT teacher head0.348
Teacher spread0.251 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations12
Published2013
Admission routes1
Has abstractyes

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