'I feel out of place' : children born into the Lord's Resistance Army and the politics of belonging
Bibliographic record
Abstract
In the aftermath of nearly three decades of conflict in northern Uganda, children born into the rebel group the Lord’s Resistance Army (LRA) experience social, economic, and political exclusion. Thousands were born to mothers and often fathers who were abducted by the LRA and forced to marry inside the rebel group. The children are part of a global population of people born of sexual violence in conflict. This dissertation contributes to the small but growing body of work on this population called ‘children born of war.’ Using a child-centered methodology, this study is grounded in the everyday experiences of 29 children born into the LRA, with data collected at various points over a period of eight months between 2011 and 2016 in northern Uganda. The following research questions guided my inquiry: 1) How do the children experience their everyday social lives? 2) How do they make sense of their experiences? 3) What strategies and resources do they use or access to help navigate their everyday lives? 4) What macro and micro processes lend insight into or explain these experiences? To answer these questions, I developed a conceptual framework consisting of the ideas of a) the politics of belonging, inclusive of place-based, and b) nation-building and hegemonic masculinity. The findings point to the role of place-making in shaping the children’s social experiences. Careful examination of their everyday lives reveals the children’s efforts to negotiate the boundaries of their exclusion in effort to navigate toward better positions in life. Through drawings, journals, storytelling, and play, I interpret how the children make sense of their experiences and construct a sense of legitimacy despite their marginalization. By situating their experiences within current and historical political forces, their everyday experiences become intelligible as central to a local and national politics of belonging.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.017 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".