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Record W1989524472 · doi:10.1080/01459740.2015.1038344

“Once a Soldier, a Soldier Forever”: Exiled Zimbabwean Soldiers in South Africa

2015· article· en· W1989524472 on OpenAlexfundno aff
Godfrey Maringira, Lorena Núñez

Bibliographic record

VenueMedical Anthropology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
FundersAddis Ababa UniversityBritish AcademyCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorInternational Development Research CentreCarnegie Corporation of New York
KeywordsContext (archaeology)Intervention (counseling)CriminologyPolitical scienceMilitary personnelGender studiesSociologyLawHistoryMedicinePsychiatryArchaeology

Abstract

fetched live from OpenAlex

Through military training, soldiers' bodies are shaped and prepared for war and military-related duties. In the context these former Zimbabwean soldiers find themselves--that of desertion and 'underground life' in exile in South Africa--their military-trained bodies and military skills are their only resource. In this article, we explore the ways in which former soldiers maintain and 'reuse' their military-trained bodies in South Africa for survival, in a context of high unemployment and a violent, inner-city environment. We look at their social world and practices of soldiering--a term that refers to the specific forms of their social interaction in exile, through which they keep their memories of their military past alive. By attending to their subjectivities and the endurance of their masculine military identities and bodies, we aim to contribute to the discussion on demilitarization, which has largely focused on the failure of models of intervention to assist ex-combatants in postconflict contexts.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.006
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.076
GPT teacher head0.355
Teacher spread0.280 · 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 designQualitative
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

Citations15
Published2015
Admission routes1
Has abstractyes

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