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Record W72888769

Transitioning Fragile States: A Sequencing Approach

2013· article· en· W72888769 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue˜The œFletcher forum of world affairs · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHIV/AIDS Impact and Responses
Canadian institutionsCarleton University
Fundersnot available
KeywordsLegitimacyVariety (cybernetics)Per capitaState (computer science)Political sciencePoliticsDevelopment economicsFragilityPolitical economyEconomic growthEconomicsPopulationSociologyLaw
DOInot available

Abstract

fetched live from OpenAlex

Fragile states are a broadly understood concept, within which one may include a variety of related terms including, but not limited to: weak states, failing and states, collapsed states, difficult partners, difficult environments, and Low Income Countries Under Stress (LICUS).1 Fragile states lack the functional authority to provide basic security within their borders, the institutional capacity to provide basic social needs for their populations, and/or the political legitimacy to effectively represent their citizens at home and abroad. Although considerable research and resources have been devoted to states in the last two decades, a lack of time series data on state has prevented researchers from examining why certain countries remain trapped in for extended periods of time, while others move in and out of fragility, or yet still, why some countries exit and are now emergent or stabilized. This article will tackle this issue by examining case studies of three types of states. In evaluating our data over more than a thirty-year period, we find that several countries are part of a group of and states that are perpetually stuck in a fragility trap. These countries show little indication of lifting themselves out of their political, economic, and social malaise; they are some of the biggest recipients of Western aid dollars and, despite being resource rich in some cases, have the lowest per capita incomes in the world. Given that some of the worst performers have experienced protracted conflict, the real costs associated with these countries is much higher than simply tallying aid figures-instead, conflict management, regional instability, and loss of life and infrastructure must be factored in.Fragile states, including those that are trapped, represent an unmet challenge to social science and policy; dominant frameworks and projects do not satisfactorily explain their dynamics and changes over time.2 These states are a compelling area of study for several policy-relevant reasons. First, they are by definition characterized by unstable policy environments, which make engagement a long-term challenge. Second, they are defined by their level of structural complexity, making policy intervention difficult. Third, neglecting states can be extremely costly in terms of poverty, the spread of disease and crime, and in terms of their impact on neighboring countries. Fourth, populations living in states are further from achieving the Millennium Development Goals (MDGs) than any others on the planet.3In this paper, state can be understood as a composite measure of all aspects of state performance, producing a ranking that would be most closely associated with those countries that have typically failed at the top of the list. This would be a list that most policymakers and academics would recognize, and indeed if one surveys the vast literature on and the various rankings available it is clear that such lists do not vary considerably in terms of which countries appear at the top.4 Cases such as Somalia, Afghanistan, the Democratic Republic of Congo (DRC), and Sudan are perpetually present regardless of which index is consulted. Most of the thirty to fifty so-called fragile states are experiencing or have experienced large-scale violence, and most suffer from internal challenges to their authority structures. The result to date has been a number of studies that limit themselves mostly to a specific case study approach. Though clearly valuable, this methodological choice has limited our understanding of the broader context of state processes. Without a suitable integrative and comparative framework, research conducted from a theoretical perspective on states cannot provide the proper context for sound resource allocation.5Our program of research is premised on the idea that state is a convergence of structural changes and events that might include large-scale conflict, disengaged leadership, failure to provide long-term service delivery, or the loss of legitimacy leading to political collapse. …

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.563
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.023
GPT teacher head0.211
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it