Self-sacrificing mothers as revered deities of social policy initiatives: reflections on the Huastec mother goddess and conditional cash transfer programmes
Bibliographic record
Abstract
This paper explains how an object – a sculpture of a Huastec goddess – has caused me to reflect differently on my doctoral dissertation work and how it has contributed to my research by helping to challenge and develop existing qualitative research methods used in my project. My research project investigates gender equality in the context of conditional cash transfers in Argentina in order to investigate whether they are empowering women. The sculpture of the Huastec Goddess has impacted on my research methods in different ways. Firstly, it has allowed me to emphasise the instrumentalisation of beneficiary women. Secondly, the Huastec sculpture has challenged my epistemological assumptions. Finally, the Huastec sculpture as an object moving from culture to culture and ending up in a museum as a collected artifact has encouraged me to think more carefully about the ethical implications of qualitative research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".