Why Organizations Fight: Wars of Choice in an Age of Instability
Bibliographic record
Abstract
Why Organizations Fight: Wars of Choice in an Age of Instability examines the participation of three international organizations, the United Nations, the North Atlantic Treaty Organization, and the European Union, across three wars: The War in Afghanistan, the War in Libya, and the War in Iraq. Each of these organizations have, as their mandate, crisis management and crisis response. As such, states have a number of organizational frameworks that they can select from. However, given the overlap in mandates, the organization that is chosen to lead is not necessarily a given. When an organization is selected by a state, or group of states, for a mission, that organization may find itself in a conflict zone that falls far beyond its initial scope and mandate. How did it come to be, for example, that NATO, a regional collective defence organization, would find itself fighting an insurgency in Afghanistan? Why, in spite of strong member-state preferences for an EU-led response in Libya, was NATO given the lead? And why did the United States, the preeminent military power, go to such lengths to try and secure a United Nations Security Council mandate for actions against Iraq? In asking these three questions, this dissertation is based on a much broader question: How are the roles of international organizations negotiated in large-scale international conflict? This dissertation argues that international organizations play an active role in shaping policy and outcomes on the battlefield. Although one may expect organizations to represent the interests of their membership, this is not always the case. Driven by their interest in survival, organizations must continuously demonstrate both material and political relevance. But demonstrating relevance is not always a straightforward process. Ensuring the survival of an organization requires navigating a complex security environment with a multiplicity of competing, and sometimes contradictory, interests.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.032 | 0.063 |
| Scholarly communication | 0.027 | 0.034 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 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".