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Record W6955935696 · doi:10.5878/000433

Working conditions and health at call centres in Sweden

2013· dataset· en· W6955935696 on OpenAlexaff

Bibliographic record

VenueSwedish National Data Service · 2013
Typedataset
Languageen
Field
Topic
Canadian institutionsInstitute for Work & Health
Fundersnot available
KeywordsWork (physics)Call centreGeneral partnershipOccupational safety and healthPhonePsychosocialWorking populationPopulationHealth care

Abstract

fetched live from OpenAlex

There are a range of problems associated with job on call centres. A range of problems associated with the job have become apparent, with time pressure, performance monitoring via computer, monitoring of phone calls, ergonomic deficiencies and musculoskeletal problems amongst the problems reported. An earlier study of a call centre in Sweden found inadequate working conditions and signs of ill health amongst a high percentage of the population in their 20s who had only been working for 2-3 years. The situation was worse there than amongst older employees in other industries with computer-intensive jobs. Inadequate working conditions and the high incidence of medical complaints amongst young employees may mean that call centres are failing to provide the sustainable work opportunities that many are counting on, e.g. in rural areas. Scientific studies of call centres are few and the state of knowledge of working conditions and health there is deficient. A cross-sectional study into working and health conditions at call centres in Sweden was conducted with the aim of contributing to a sustainable development of call centre work. The project was conducted in partnership with the Ergonomics Programme at the National Institute for Working Life, Occupational Medicine North, Sundsvall Hospital, and the Institute for Psychosocial Factors and Health at the Karolinska Institute. Data were collated at social, corporate and individual level from 15-20 larger call centres with different operating spheres, ownership structures and geographical location. Data were collected on work organisation, content and times, physical and psychosocial working conditions, and health and well-being with the aid of questionnaires, observations, measurements, medical examinations and company registers (including the computerised monitoring system). A total of approximately 1,500 people were included in the study. Models were tried out in order to evaluate the effects of ill health and inadequacies in working conditions at the company's expense.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.370
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.009

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 head0.138
GPT teacher head0.378
Teacher spread0.240 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2013
Admission routes1
Has abstractyes

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