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Record W2290191231

How may I help you?: an ethnographic view of contact-center HCI

2008· article· en· W2290191231 on OpenAlexaff
Howard Kiewe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsMcGill University
Fundersnot available
KeywordsWorkflowTask (project management)Context (archaeology)EthnographyStandardizationHuman–computer interactionKnowledge managementComputer scienceParticipant observationCenter (category theory)SoftwareUser experience designCognitionPsychologySociologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

www.kieweconsulting.com This study used an applied ethnographic research method to investigate human-computer interaction (HCI) between call center agents and agent-facing software in the context of contact-center culture. Twenty semi-structured interviews were completed, along with non-participant observation at two contact centers, one that followed a user-centered design (UCD) process for software development and another that did not. Agent productivity and satisfaction at the non-UCD center were hampered by poor task-UI integration, ambiguous text labels, and inadequate UI standardization. Agents required multiple applications to complete a single task, leading to long task times and cognitive strain. In contrast, the UCD center used a unified UI that reduced task times and decreased cognitive strain. In both centers, the workflow was reported to be stressful at times; however, management at both companies employed high involvement work processes that mitigated this stress. Implications for possible high-involvement UI design are considered and a strategy for applied ethnographic research is discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.081
GPT teacher head0.357
Teacher spread0.276 · 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 designNot applicable
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
Published2008
Admission routes1
Has abstractyes

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