MétaCan
Menu
Back to cohort
Record W2556040428 · doi:10.1080/02533952.2016.1238390

Political violence within army barracks: desertion and loss among exiled Zimbabwean soldiers in South Africa

2016· article· en· W2556040428 on OpenAlexfundno aff
Godfrey Maringira

Bibliographic record

VenueSocial Dynamics · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican studies and sociopolitical issues
Canadian institutionsnot available
FundersInternational Development Research CentreElectronics Research Laboratory, Volkswagen of AmericaHarry Frank Guggenheim FoundationCarnegie Corporation of New York
KeywordsPoliticsReification (Marxism)PsycheInstitutionCriminologyMindsetSociologyLawGender studiesPolitical scienceHistoryPsychologyPsychoanalysis

Abstract

fetched live from OpenAlex

While studies on soldiers who leave the army have focused on them as perpetrators of political violence in war and peace, little is known about the ways in which soldiers have been subjected to violence. This paper examines the ways in which Zimbabwe National Army deserters who are currently in exile in South Africa experienced politically inspired violence in the army barracks and the ways in which they mediate and reify it through the image of the “torn underwear.” The ‘torn underwear’ signifies the violence experienced in the army barracks but also represents its reification in their present exile condition and the ways in which it is embedded in the body psyche. In analysing the army barracks as a ‘total institution’ and as a ‘surveillance unit,’ the paper, respectively, situates itself in the discussions of Goffman and Foucault, drawing from life history interviews and conversations with deserters who live in exile in South Africa.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.006
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.286
Teacher spread0.270 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueSocial DynamicsSame topicAfrican studies and sociopolitical issuesFrench-language works237,207