Bibliographic record
Abstract
Purpose This paper aims to focus on the communications skills training given to transnational call center workers in India whose jobs involve providing customer service to Western customers. Emotion work is a key component of customer service jobs, and this work is constructed as an important soft skill. Design/methodology/approach Between 2002 and 2009, 100 interviews were conducted with customer service workers, trainers and managers in India. Respondents provided detailed descriptions of their training curricula and some workers shared their complete set of training booklets. The analysis for this paper is based on a section of the curricula that focuses on communication skills used during training programs for Indian customer service agents. Findings Training curricula designed to enhance the communication skills of call center agents are vehicles through which workers learn to make sense of their place in social, economic and cross‐national hierarchies. Research limitations/implications The study of emotion work in relation to workplace learning occurs in the context of global economic regimes. Originality/value Training curricula on communication skills serves to help workers to cope with the expression of customer abuse. Rather, there is a need to develop regulations that protect workers from customer aggression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".