Kazakhstan – Challenges to the Booming Petro-Economy FAST Country Risk Profile Kazakhstan
Bibliographic record
Abstract
swisspeace is an action-oriented peace research institute with headquarters in Bern, Switzerland. It aims to prevent the outbreak of violent conflicts and to enable sustainable conflict transformation. swisspeace sees itself as a center of excellence and an information platform in the areas of conflict analysis and peacebuilding. We conduct research on the causes of war and violent conflict, develop tools for early recognition of tensions, and formulate conflict mitigation and peacebuilding strategies. swisspeace contributes to information exchange and networking on current issues of peace and security policy through its analyses and reports as well as meetings and conferences. swisspeace was founded in 1988 as the “Swiss Peace Foundation ” with the goal of promoting independent peace research in Switzerland. Today swisspeace engages about 35 staff members. Its most important clients include the Swiss Federal Department of Foreign Affairs (DFA) and the Swiss National Science Foundation. Its activities are further assisted by contributions from its Support Association. The supreme swisspeace body is the Foundation Council, which is comprised of representatives from politics, science, and the government. FAST – Early Analysis of Tensions and Fact-Finding FAST, swisspeace's early warning system, was developed in 1998 for the Swiss Agency for Development and Cooperation (SDC) of the Swiss Federal Department of Foreign Affairs (DFA). In the meantime the Swedish, Austrian, Canadian, and US development agencies have joined what is now known as FAST International. FAST focuses on the early detection of critical political developments to allow for the prevention of violent conflicts or the mitigation of their consequences. FAST monitoring is, however, not limited to anticipating adverse developments: The system also highlights windows of opportunity for peacebuilding. Currently, FAST covers 25 countries in Central and South Asia as well as Africa and Europe. For more detailed information on FAST International, please refer to: www.swisspeace.org/fast.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".