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Record W1517752269

Shake Hands with the Devil: The Failure of Humanity in Rwanda

2014· article· en· W1517752269 on OpenAlexaboutno aff
Patricia C. Murphy

Bibliographic record

VenueMilitary review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGenocideHumanityEthnic groupCrimes against humanityLawPolitical scienceCriminologySociologyWar crimeInternational law
DOInot available

Abstract

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SHAKE HANDS WITH THE DEVIL: The Failure of Humanity in Rwanda Romeo A. Dallaire and Brent Beardsley, Carroll & Graf, New York, 2004, 584 pages, $32.99 Atrocious crimes against humanity in Rwanda began in 1993 when organized groups of the ethnic Hutu majority embarked upon a campaign of genocide against the ethnic Tutsi minority. This was done at a time when relatively few U.N. forces were on site to intervene in the subsequent massacres. In spite of his insistence that military reinforcements were necessary to prevent and stop the brutal killings, Lt. Gen. Romeo Dallaire, commander-designate of the U.N. Assistance Mission in Rwanda (UNAMIR), did not receive any additional resources to assist his small number of troops in protecting the Tutsi victims. As a result, the local government that perpetrated the mass killings was unopposed by any organized defensive force or by international military forces. The result was the murder of over 800,000 Rwandan Tutsis and moderate Hutus. Following his tour in Rwanda and retirement from the Canadian armed forces, Dallaire documented his experience and provided readers with an intimate tale recounting the time he spent in Rwanda during the attempted genocide of the Tutsi ethnic minority. His story begins with the invitation for him to accept command of UNAMIR, continues with an explanation of the U.N's lack of preparation for the mission, and focuses on his direct observations of the mass atrocities as they unfolded. In his account, Dallaire provides an elaborate and thorough explanation of the emotions and justification behind his decisions. He lists his actions and the associated motivation behind them. What is particularly interesting is his insight into the actions he opted not to take. He explains in detail the potential outcomes that may have resulted had he made different choices such as attempting to stop the Rwandan military forces as they were arming to commit genocidal acts. The story serves as an incredible tale from the most powerful representative of the U.N. and Western society who personally witnessed repeated, vicious violations of human rights during the Rwandan genocide. One of Dallaire's prominent themes is that powerful nations must decide whether they will waive the justification for intervention based on national interests, and instead become involved in foreign affairs based on humanitarian concerns. He provides insight into the severe complications that arise for world leaders as they must consider the consequences of their decisions. A passionate human rights advocate and critic of the U.N. as well as U.S. policy toward Rwanda during the unfolding events, Samantha Powers, wrote the foreword for this book. Although her accounts of the U.N. and U.S. failure to intervene are strongly supported with facts, her argument that they failed in their duty to intervene does not consider other perspectives and the associated rationale behind the actions of all parties which were involved. Moreover, her sympathetic approach to Dallaires story is one-sided and she does not acknowledge other conditions that may have influenced the international community's decision not to intervene. In contrast, journalist Gil Courtemanche opines that fault for the outcome lies in part with Dallaire who, he asserts, was too methodical and did not possess adequate initiative and critical thinking required of an effective UNAMIR commander. …

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.008
Scholarly communication0.0040.005
Open science0.0010.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.012
GPT teacher head0.269
Teacher spread0.257 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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