MétaCan
Menu
Back to cohort
Record W4238538093 · doi:10.32920/14652774

Examination of deep acting in retail disability service training

2021· preprint· en· W4238538093 on OpenAlexaff

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEmotional laborTraining (meteorology)Service (business)Scale (ratio)Quality (philosophy)PsychologyBusinessMarketingApplied psychologySocial psychology

Abstract

fetched live from OpenAlex

The quality of retail service delivered to disabled customers is affected by employees’ behaviour and attitudes. These behaviours are related to employees’ ability to manage their emotional reactions (referred to as emotional labour) to disabled customers’ varied and personalized needs. Although retailers provide disability training, employees utilize varied levels of emotional labour skills (referred to as deep acting) in interactions with disabled customers. Studies call on employers to improve disability training for employees, so that they can manage their emotional labour and disabled customers can receive higher quality service. This study addresses the question of whether training activities influence retail employees’ deep acting skills at various levels when providing services to disabled customers. By adapting Brotheridge & Lee's (2003) Emotional Labor Scale and Saks and Belcourt's (2006) Training Activities Scale, 150 participants filled a questionnaire and were grouped into three categorical levels based on their deep acting skills prior to training. The results show a positive influence exists between activities during and after training and deep acting skill levels. This study calls on retail organizations to identify employees with positive refocus and basic levels of deep acting and invest more in during and after training stages to facilitate the transfer of deep acting skills.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
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 integrity0.0000.001
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 head0.127
GPT teacher head0.384
Teacher spread0.258 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicEmotional Labor in ProfessionsFrench-language works237,207