‘The Synergy Between You’: Mothers, Nannies, and Collaborative Caregiving in Contemporary Matroethnographies
Bibliographic record
Abstract
In this article I examine representations of mother/caregiver relationships in what I am calling a new genre: matroethnography. The term fuses the prefix matro (Latin root for mater) with ethnography; and further, signals a conflation of matro with the auto (autobiography) in autoethnography, itself a hybrid genre from the fields of life writing, anthropology, and sociology. Driven by auto/biographical and autoethnographical impulses, matroethnographies record maternal subjectivities that are individual and collective, personal and communal. I focus on a cluster of matroethnographies published mainly in the last fifteen years that bring together an array of mothers, who are typically white, middle- to upper-class, and Anglo-American; and caregivers, who are typically racialized, low-income-earning, and frequently (illegal) immigrants, and who are often mothers themselves. Utilising innovative combinations of interviews, testimonials, scholarship, and creative non-fiction storytelling, these matroethnographies radically re-position the mother (the traditional primary nurturer) in dialogue with her child's waged caregiver. In so doing, the texts inscribe, negotiate, and critique prevailing twenty-first-century maternal practices, identities, and ideologies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".