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Record W4303578820 · doi:10.5430/wjel.v12n8p127

Surrogacy: A Bio-economical Exploitation of Proletariats in Amulya Malladi’s A House for Happy Mothers

2022· article· en· W4303578820 on OpenAlexvenueno aff
C. Suganya, M Vijayakumar

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsCommodificationPovertyAlienationCompensation (psychology)Egg donationEconomic growthPolitical scienceSociologyBusinessLawMedicinePsychologyEconomicsEconomyGynecologySocial psychology

Abstract

fetched live from OpenAlex

Infertility remains a threat to global health issues thus the remedy is global with the medical advancements in technology that enable infertile couples to have babies through surrogacy. Surrogacy is a legal practice of hiring a woman’s womb for bearing a child to infertile parents where the intended parents claim full parental rights and the surrogate mothers get the monetary compensation in commercial gestational surrogacy. Surrogates are proletariats from third-world countries struggling to meet day-to-day ends, whilst intended parents are from first-world countries. The existence of poverty and poor economy avail abundant surrogates in third world countries like India attracts infertile couples to flock to these countries thus surrogacy clinics and agents practice exploitative surrogacy (baby) business. This article unveils the exploitation of poor surrogate women and their bodies, with reference to Amulya Malladi’s A House for Happy Mothers (2016). Further, this study attempts to evaluate surrogacy with the theoretical framework of Marxist Theory of Alienation or Estrangement which condemns the poor surrogates as reproductive machines (lobourers) and commercial surrogacy as commodification of wombs.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.287
Teacher spread0.267 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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