Bibliographic record
Abstract
The first Canadian diplomat to be posted to war-torn Sudan, Nicholas Coghlan was a natural choice to lead Canada’s representation in the new Republic of South Sudan soon after the country was founded in 2011. In late 2013 Coghlan and his wife Jenny were in the capital, Juba, when it erupted in gunfire and civil war pitted one half of the army against the other, Vice-President Machar against President Kiir, and the Nuer tribe against the Dinka. This action-focused narrative, grounded by accounts of meetings with key leaders and travels throughout the dangerous, impoverished hinterland of South Sudan, explains what happened in December 2013 and why. In harrowing terms, Collapse of a Country describes the ebb and flow of the war and the humanitarian tragedy that followed, the Coghlans’ scramble to evacuate South-Sudanese Canadians from Juba, and the well-meant but often ill-conceived attempts of the international community to mitigate the misery and bring peace back to a land that has rarely known it. Coghlan’s stark narrative serves as a lesson to politicians, diplomats, aid workers, and practitioners on the breakdown of governance and relationships between ethnic groups, and the often decisive role of international development representatives. Fast-paced and poignant, Collapse of a Country gives an insider’s glimpse into the chaos, violence, and ethnic conflicts that emerged out of a civil war that has been largely ignored by the West.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.014 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".