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Record W2932513400 · doi:10.24251/hicss.2019.805

ICT, Permeability Between the Spheres of Life and Psychological Distress Among Lawyers

2019· article· en· W2932513400 on OpenAlexaff
Nathalie Cadieux, Elaine Mosconi, Nancy Youssef

Bibliographic record

VenueProceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · 2019
Typearticle
Languageen
FieldPsychology
TopicTechnostress in Professional Settings
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsInformation and Communications TechnologyTechnostressDistressPacePsychologyWorkloadPsychological distressThematic analysisThe InternetQualitative researchMisinformationApplied psychologySocial psychologyPublic relationsAnxietySociologyPolitical scienceClinical psychologyComputer scienceSocial scienceLaw

Abstract

fetched live from OpenAlex

The pervasiveness of information and communications technologies (ICT) has changed the nature of work in recent decades. Positive and negative impacts of ICT have been identified in every profession, including among lawyers. This paper examines the impact of ICT on the working conditions, stress and psychological distress experienced by lawyers, based on a qualitative study. Twenty-two (22) interviews were conducted with the aim of gaining a deep understanding of this issue. A thematic content analysis of the interviews revealed that factors related to ICT appear to contribute to the overall stress (technostress and other stress) experienced by lawyers, in turn leading to psychological distress. Moreover, the growing permeability between the different spheres of life caused by ICT and their particular characteristics has increased the workload of lawyers and accelerated their pace of work. Participants also identified frequent technological problems, as well as clients’ misinformation on the Internet, as risk factors.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.347
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

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 designObservational
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

Citations2
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System SciencesSame topicTechnostress in Professional SettingsFrench-language works237,207