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Record W4312719890 · doi:10.17705/1cais.05139

Global Perspectives on IT Occupational Culture: A Three-Way Cultural Analysis

2022· article· en· W4312719890 on OpenAlexaff
Tim Jacks, Prashant Palvia, Alexander Serenko, Jaideep Ghosh

Bibliographic record

VenueCommunications of the Association for Information Systems · 2022
Typearticle
Languageen
FieldPsychology
TopicTechnostress in Professional Settings
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsReverenceAutonomyValue (mathematics)SociologyPerspective (graphical)IdeologyPublic relationsOrganizational cultureKnowledge managementSocial sciencePolitical scienceComputer sciencePolitics

Abstract

fetched live from OpenAlex

This study examines the occupational values of IT professionals across the world. Using the three-way perspective of cultural theory as 1) integrated, 2) differentiated, and 3) fragmented allows for a more comprehensive view of IT Occupational Culture (ITOC). Conducted under the auspices of the World IT Project, survey responses were gathered from more than 10,000 IT workers in 37 different countries. The findings provide global-based support for the ITOC ideology of values: Autonomy in Decision-Making, Structure in the Workplace, Precision in Communication, Innovation in Technology, Reverence for Technical Knowledge, and Enjoyment at the Workplace (abbreviated as ASPIRE). The most important value was Reverence for Technical Knowledge. ITOC is both more homogeneous and, at the same time, more complex than originally thought. While there are surprising global similarities in ITOC around the world, there are also important differences, which may be due to national culture, especially with regard to Structure in the Workplace and Precision in Communication. A better understanding of ITOC around the world should help reduce the amount of cultural clash between IT departments and business management.

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)0.006
metaresearch head score (Gemma)0.005
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 score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.006
Science and technology studies0.0030.006
Scholarly communication0.0060.003
Open science0.0000.006
Research integrity0.0000.001
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 head0.041
GPT teacher head0.378
Teacher spread0.337 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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