Research assistants, reflexivity and the politics of fieldwork in urban Pakistan
Bibliographic record
Abstract
In this paper, we discuss the politics of fieldwork in urban Pakistan and in doing so draw attention to the role of research assistants (RAs) in the production of knowledge. The discussion explores how the roles, reflexivity and positionality of our three Muslim female RAs adds depth to our understanding of fieldwork in a culturally and politically charged urban setting where everyday violence combined with wealth asymmetries and anxieties over religious identity add layers of complexity in researcher–respondent working relationships. This generates a process of negotiation over ethical dilemmas that are not easily surmounted and complicates how we think about transformations in the production of knowledge. We use the notion of the ‘triple subjectivity’ of fieldwork to problematise the positionality of researchers and the people they seek to represent through translations of language, contexts and encounters. Moreover, we underscore that the positionality of our RAs was strongly influenced by religion, ethnicity and class. Notably, state directives have played an important role in the way relationships are forged in the field, whereby ethnic–religious minorities have been categorised and treated in distinct ways. Our RAs’ knowledge of marginalised communities increased significantly with time spent in the field, but they still retained specific understandings of difference. This awareness was a crucial learning experience and prompted our RAs to become mindful of their own investment and contribution to the process of ethnographic engagements. Our objective in this paper is to reveal the tensions and possibilities generated by the triple subjectivities involved in our fieldwork in terms of their implications for transformations of research. Above all, our RAs’ reflections demonstrate that we as researchers must remain sensitive to the emotions and anxieties of those we work alongside.
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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 | 0.078 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.035 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".