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Record W4392000286 · doi:10.5772/intechopen.1001330

Improving the Measurement of Women’s Work: The Contribution of Demographic Surveys in Francophone West Africa

2023· book-chapter· en· W4392000286 on OpenAlex
Anne E. Calvès, Agnès Adjamagbo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIntechOpen eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of CanadaAgence Nationale de la Recherche
KeywordsContext (archaeology)Work (physics)Unpaid workWomen's workFrenchScale (ratio)FertilityEconomic growthPolitical scienceGender studiesGeographySociologyPopulationEconomicsEngineeringDemography

Abstract

fetched live from OpenAlex

Since the 1970s, the measurement and recognition of women’s work and their contributions to family well-being and economic development have been a matter of academic interest, as well as feminist advocacy. The interrelationships between women’s work and demographic processes, especially decisions regarding fertility, have also attracted the attention of demographers for some time. However, despite long-standing efforts to capture all aspects of women’s work, large-scale demographic and economic surveys conducted in the Global South still fail to approach work as a gendered concept and continue to make much of women’s labor invisible. The measurement of unpaid care and household responsibilities is particularly scarce. In such a context, the purpose of this chapter is twofold. First, it retraces the long history of the global efforts of feminist scholars and activists to enhance the measurement of women’s work. Second, it illustrates how recent data collection initiatives in francophone West Africa, building on the experience of collaborative research conducted by demographers in the region since the 1970s, have attempted to fill some of the persisting gaps in data on women’s activity, especially on household domestic and care, voluntary collective/community work, as well as on women’s contribution to household expenses and family support.

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.

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)0.018
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.277
Teacher spread0.230 · 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