Ambivalent complicities and knowledge production: Researching migrant women farmers' reproductive health experiences in the middle belt of Ghana
Bibliographic record
Abstract
Using a critical reflexive process (An Invitation to Reflexive Sociology, 1992; Theory, Culture & Society, 13, 1996, 17), this article identifies and examines issues of power, complicity and knowledge production as they emerged in the first author's master's research on migrant women farmers' economic and reproductive health experiences in the middle belt of Ghana. We examine the ambivalent positionality of the international graduate student researcher as "other of the other" (Signs: Journal of Women in Culture and Society, 30, 2005, 2017, p. 2025), and how diverse fields of power, including the researcher's educational institution and cultural norms regarding gender relations, mediated interactions among various actors in the research process. Specifically, we examine how the student researcher was complicit in reinforcing patriarchal standards, perpetuating western saviourism and committing symbolic violence. Situating these reflexive findings in relation to insights from feminist postcolonial theories, we highlight how power relations, gender and social class informed these ambivalent complicities. Rather than erase/silence these tensions in the research process, we argue that such ambivalences may be an inevitable dimension of transnational knowledge creation, and thus, it is imperative that researchers consider how their ambivalent positionalities and complicities may be navigated and leveraged most productively and with the least harm to research participants.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.030 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".