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Record W1595676723

The Rise of the Relief-and-Reconstruction Complex

2006· article· en· W1595676723 on OpenAlexaboutno aff
Walden Bello

Bibliographic record

VenueJournal of international affairs · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsMilitantHumanitarian aidPoliticsPolitical scienceRelief WorkPolitical economySociologyPublic relationsLaw
DOInot available

Abstract

fetched live from OpenAlex

Massive infrastructure damage and great social dislocation have been common consequences of natural disasters and social disasters like wars. Up until a few years ago, the aims of and reconstruction efforts were fairly simple: immediate physical of victims, reduction of social dislocation, restoration of a functioning social organization and reparation of physical infrastructure. In major disasters or wars, international actors were central players--most prominently United Nations agencies and the Red Cross Movement. In recent years, however, the objectives of both disaster and post-conflict reconstruction have become more complex. Strategic considerations have become more prevalent in military-led disaster operations. Post-disaster and post-conflict reconstruction planning and implementation are increasingly influenced by neoliberal market economics. A new militant humanitarianism infuses not only post-conflict reconstruction work but, in a number of cases, has itself helped to precipitate conflicts. Disaster and post-conflict reconstruction have thus become increasingly intertwined, so that it is difficult to understand the dynamics of one arena without looking at the other. This is all the more true since the same set of actors now dominate both arenas: the U.S. military-political command, the World Bank, corporate contractors and humanitarian and development non-governmental organizations (NGOs). Humanitarian missions led by the United Nations and Red Cross are a thing of the past, though these players continue to participate in and reconstruction work along, of course, with national governments. The new establishment in post-disaster and post-conflict reconstruction is what will be termed here the relief and reconstruction complex (RRC). Power structures develop legitimating ideologies, and accompanying the rise of the RRC is a formulaic discourse that is built on appeals to national and international security, neoliberal economics and a burgeoning, militant rights-based humanitarianism. THE TSUNAMI AS OPPORTUNITY I: THE PENTAGON Within hours after the massive tsunami that hit at least eleven countries bordering the Indian Ocean on 26 December 2004, U.S. Navy Orion reconnaissance aircraft began flying over the affected areas to deliver emergency and to assess the damage. This was the prelude to a massive expedition that eventually came to encompass more than twenty-four U.S. warships, over 100 aircraft and some 16,000 military personnel--the largest U.S. military concentration in Asia since the end of the Vietnam War. (1) It was not a disinterested peacetime military mission. One immediate sign of this was the deliberate U.S. effort to marginalize the United Nations, which was expected by many to coordinate, at least at the formal level, the effort. Instead, Washington sought to bypass the United Nations by setting up a separate assistance consortium with India, Australia, Japan, Canada and several other governments, with the U.S. military task force's Combined Coordination Center at U Tapao, Thailand, effectively serving as the axis of the whole operation. (2) Showing the flag was seen by the Bush administration as an important objective in light of the low point in the relations between the United States and many communities in the Southeast Asian region owing to the War on Terror, which many Muslims, who were in the majority in the most devastated country, Indonesia, had seen as being directed against them. The War on Iraq was also universally unpopular throughout the area, yet here was an opportunity to show a different face of the U.S. military than that of a force imposing a harsh military occupation on that Middle Eastern country. However, there were more immediate military objectives as well. The Indonesian military had been subject to a ban on U.S. arms sales as well as restrictions on U. …

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0090.016
Scholarly communication0.0160.014
Open science0.0020.020
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0340.003

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 head0.008
GPT teacher head0.259
Teacher spread0.251 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations41
Published2006
Admission routes1
Has abstractyes

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