A reflection on ethical and methodological challenges encountered during a critical ethnographic study with various Rwandan society members on unintended adolescent pregnancies
Bibliographic record
Abstract
Conducting research studies with vulnerable populations on sensitive topics such as adolescent pregnancy can be challenging depending on methodological approaches and ethical issues that may arise before, during, and after data collection. This methodological paper was developed based on experiences and lessons learned from a critical ethnographic study conducted to determine and understand the cultural and personal meaning of unintended adolescent pregnancy in the Rwandan context and to explore the perceived consequences and management of unintended adolescent pregnancy with and for single adolescent mothers. The purpose of this methodological paper is to discuss methodological and ethical challenges encountered while conducting this research, as well as various approaches used to overcome these challenges, and to provide guidance to researchers interested in conducting research about similar or other sensitive topics. Future researchers facing similar challenges should prioritize community engagement strategies, such as building strong relationships with gatekeepers and leaders, to facilitate access to potential participants. Additionally, researchers should engage in continuous ethical reflection and adaptation throughout the study, adjusting strategies if necessary to ensure the well-being and autonomy of participants. As a result of the practical and methodological strategies provided in this reflective paper, researchers could be able to navigate practical, methodological, and ethical challenges effectively while conducting sensitive studies on topics such as adolescent pregnancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.134 | 0.145 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.028 | 0.043 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.005 | 0.018 |
| Research integrity | 0.009 | 0.024 |
| 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".