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Record W4413906628 · doi:10.70121/001c.143862

For Better or For Worse? The Dual Economic Impact of the Industrial Revolution on Women

2025· article· en· W4413906628 on OpenAlexaff

Bibliographic record

VenueScholarly review . · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsDoug Bragg Enterprises (Canada)
Fundersnot available
KeywordsDual (grammatical number)Industrial RevolutionEconomicsPolitical scienceArt

Abstract

fetched live from OpenAlex

This paper examines the economic impact of the Industrial Revolution on the lives of working-class and middle-class women. It describes pre-industrial society, where family members laboured together to earn a living in a system known as the family economy. Industrialization disrupted this way of living by moving production from the household into factories. The family wage economy, where individual members laboured for wages to contribute to a common fund, soon replaced the family economy. This paper examines how industrialization changed the lives of women in Britain, France, and the US and finds that the impacts were often divergent. While factory work subjected working-class women to exploitative conditions, low pay, and exclusion from unions, it also provided them with greater independence from the family. In the middle class, the rise of the Cult of Domesticity granted women authority in the domestic sphere and offered new opportunities for female solidarity, but also reinforced restrictive gender norms. This paper argues that the short-term impacts of the Industrial Revolution, both the beneficial and the harmful, catalyzed long-term social change by awakening women’s feminine consciousness.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.063
GPT teacher head0.358
Teacher spread0.295 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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