Finding Your Feet in the Field: Critical Reflections of Early Career Researchers on Field Research in Transitional Societies
Bibliographic record
Abstract
Fieldwork that takes place in conflict or transitional regions is becoming increasingly popular amongst early-career and more seasoned researchers, but is an area that retains an air of mystery and remains an exotic form of knowledge gathering. There exists a paucity of personal reflection on the challenges associated with conducting fieldwork in conflicted or transitional regions and a limited amount of insight into the practical steps taken in advance of and when immersed in the field. Such reticence to share honest fieldwork experiences, particularly the more challenging research that takes place in conflict or transitional settings, plays a part in creating a culture of silence. This paper attempts to counteract this silence by drawing on the challenges experienced by two early career researchers conducting fieldwork in Uganda and Palestine, focusing on the practical steps taken in advance of entering the field, and the challenges faced whilst engaged in fieldwork. Specific challenges are highlighted throughout, including physical access to areas in conflict, engaging with reluctant research participants, the emotional impact of fieldwork on the researcher, maintaining confidentiality, researching with vulnerable victims, and ensuring appropriate knowledge exchange between researchers and participants. The paper concludes by emphasising the requirement for greater reflection on the inherently personal challenges associated with conducting fieldwork in conflicted or transitional settings and highlights the view that fieldwork is a privileged position that carries great responsibilities which must be upheld to ensure the sustainability of future research. This paper hopes to contribute to the wider debate on conducting fieldwork and the challenges associated with working in conflicted or transitional regions.
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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 | 0.090 | 0.167 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.061 | 0.079 |
| Scholarly communication | 0.034 | 0.022 |
| Open science | 0.008 | 0.026 |
| Research integrity | 0.020 | 0.049 |
| Insufficient payload (model declined to judge) | 0.002 | 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".