Listener perceptions of customer service agents’ performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This study investigated listener-based assessment of the job performance of second language (L2) speakers employed as customer service agents in outsourced foreign-based call centers, focusing on agents’ job performance as a function of the comprehensibility, fluency, and accentedness of their speech. Using Amazon’s Mechanical Turk crowdsourcing platform, 116 native English-speaking listeners evaluated two-minute recordings of actual customer service conversations featuring 18 Filipino agents, assessing them for three global speech dimensions (comprehensibility, accentedness, and fluency) and three performance indicators, including agents’ confidence, competence, and listeners’ interest in future communication with agents (a measure capturing customer patronage). Comprehensibility and fluency consistently predicted how the listeners assessed the agents on all job performance scales, and accentedness was additionally associated with how strongly the listeners wished to communicate with the agents. Findings generally highlight the importance of fluent and comprehensible L2 speech in workplace settings.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it