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Record W2887624265 · doi:10.25071/2369-7326.40278

Dystopian and Utopian Homecomings in Shimmer Chinodya’s Harvest of Thorns and Olley Maruma’s Coming Home

2017· article· en· W2887624265 on OpenAlexvenueno aff
Tanaka Chidora, Sheunesu Mandizvidza

Bibliographic record

VenuePivot A Journal of Interdisciplinary Studies and Thought · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican studies and sociopolitical issues
Canadian institutionsnot available
Fundersnot available
KeywordsHomecomingDystopiaNarrativeNationalismLiteratureHistoryCharacter (mathematics)SociologyArtArt historyPoliticsLawPolitical science

Abstract

fetched live from OpenAlex

The two novels chosen for this paper represent divergent versions of homecoming. Most interestingly, Harvest of Thorns (1989), a victim of scathing attack by cultural nationalists for its suggestively anti-establishmentarian title, and Coming Home (2006), are novels written at different times and feature two different characters whose versions of homecoming do not agree with their particular ‘callings’. The central character in Harvest of Thorns is an ex-guerrilla of the Second Chimurenga (war of liberation that ushered in Zimbabwe’s independence in 1980) who is depicted by the author as having failed to integrate into the ‘home’ he was fighting for. This dystopian depiction of the ‘home’ to which the central character, Benjamin, comes back after the war does not agree with the clichéd rhetoric of nationalist narrative that sees the birth of the new nation in 1980 as the pinnacle of nationalist achievement. On the contrary, Coming Home was written by a euphoric homecoming author and intellectual; his narrator is also ‘coming home’ (and celebrates all the associated nationalist utopias of that period) at a period leading towards 1980. Why would Coming Home be written in 2007 at a time when the majority of Zimbabweans were exiting home? These divergent views beg for closer analysis of the texts especially focusing on how Harvest of Thorns shatters nationalist narration while Coming Home desperately reconstructs it.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.402
Teacher spread0.356 · 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 teacher head, not a consensus.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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