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Record W2293333632

Personas als Usability-Methode in internationalen Software-Projekten

2013· article· de· W2293333632 on OpenAlexvenueno aff
Stefanie Elbeshausen, Thomas Mandl, Katrin Werner, Christa Womser‐Hacker, Wilhelm Thorsten

Bibliographic record

VenueIngénierie des systèmes d information · 2013
Typearticle
Languagede
FieldComputer Science
TopicPersona Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsUsabilityPolitical scienceHumanitiesPersonaComputer scienceArtHuman–computer interaction
DOInot available

Abstract

fetched live from OpenAlex

Bisher gibt es kaum Forschungsarbeiten daruber, wie Personas in internationalen Projekten eingesetzt werden. Studien, in denen interkulturelle Aspekte eine Rolle spielen, gehen haufig nicht auf die damit verbundenen Besonderheiten und Problematiken ein. Grundlegende Motivation fur die hier beschriebene Forschung ist daher die Zusammenfuhrung von Ergebnissen aus den Bereichen Usability und Interkulturelle Kommunikation mit den praktischen Erfahrungen, wie sie in der taglichen Praxis eines Usability-Dienstleisters haufig auftreten. Ein Schwerpunkt liegt auf der Erstellung eines Leitfadens mit Vorschlagen zur Vorgehensweise bei internationalen Software- Projekten.

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)0.054
metaresearch head score (Gemma)0.094
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.054
Threshold uncertainty score0.287

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0540.094
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0070.006
Science and technology studies0.0030.006
Scholarly communication0.0120.010
Open science0.0020.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.002

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 head0.027
GPT teacher head0.263
Teacher spread0.236 · 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 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

Citations2
Published2013
Admission routes1
Has abstractyes

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