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Record W2102262886 · doi:10.5539/ass.v8n7p157

Women in BPO Sector in India: A Study of Individual Aspirations and Environmental Challenges

2012· article· en· W2102262886 on OpenAlexvenueno aff
Dipa Dube, Indrajit Dube, Bhagwan R. Gawali, Subechhya Haldar

Bibliographic record

VenueAsian Social Science · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicIndian Economic and Social Development
Canadian institutionsnot available
Fundersnot available
KeywordsSalaryWorkforceService (business)Index (typography)BusinessWork (physics)Tertiary sector of the economyWest bengalDemographic economicsLabour economicsSocioeconomicsEconomic growthMarketingEconomicsPolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

The present paper is based on the key findings of an empirical study conducted on the BPO workforce over a period of one year in Karnataka and West Bengal in India. The objective of the study was to prepare a status report on the service conditions, benefits and hazards of working women in the BPO sector. It also attempted to draw a comparative picture of the situation in the two states vis-à-vis women employees. The study assumed significance in light of the gory incidents of rape, murder, and assault of women employees in states of Karnataka, Maharashtra and others. Women constitute a significant number of the workforce in BPO sector in the country. They are primarily in their mid-twenties and qualified with graduate or post graduate degrees. Employment opportunity and career prospects in BPOs come as an enviable choice for them. Most of the women earn a good package, especially in Bangalore where salary index is higher than Kolkata. After a brief tenure in contractual service, the employees are inducted into the permanent service of the company with diverse benefits ranging from gratuity, bonus, provident fund, allowances, insurance and others. However, it has been found that thin strains of discontentment creep in over time on issues such as inadequate salary packages, differential promotional prospects and increments, ambiguous service conditions, irregular and arduous work schedules and lack of facilities in workplace.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.048
GPT teacher head0.223
Teacher spread0.175 · 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 designObservational
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

Citations1
Published2012
Admission routes1
Has abstractyes

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