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Record W1993195764 · doi:10.1080/18125441.2011.590018

Secular study and suffering: J.M. Coetzee's “The humanities in Africa”

2011· article· en· W1993195764 on OpenAlexaff
Katherine Hallemeier

Bibliographic record

VenueScrutiny2 · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican cultural and philosophical studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsFaithHumanitiesSociologyKwameMedical humanitiesPhilosophyAestheticsTheologyAnthropology

Abstract

fetched live from OpenAlex

Abstract Prominent literary philosophers as diverse as Martha Nussbaum, Kwame Anthony Appiah, and Gayatri Chakravorty Spivak have envisioned a role for the humanities in fostering more ethical relationships on a global scale. Through a close reading of JM Coetzee's fifth “lesson” in Elizabeth Costello: eight lessons, this paper interrogates the limits of the humanities for promoting secular salvation. “Lesson five: the humanities in Africa”, I argue, troubles the distinction between secular teaching and religious faith as alternatives to living in a world imbued with suffering, by suggesting that neither the humanities nor religion materially offers an escape from suffering – that neither secular nor divine salvation exists beyond hope and faith. The lesson asks: do the humanities offer anything besides the promise of salvation to its students? If the secular salvation offered by the humanities fails to engage substantively with what one of Coetzee's characters calls “the reality of Africa”, despite calls for mutual understanding or an understanding of mutuality, how do we rethink the humanities? How do we imagine, and how might we re-imagine, the relationship between the humanities and quotidian suffering? Perhaps as obsessive, repetitive, imperfect performances, both the humanities and religion exist as rituals through which to live with others who are (also) suffering.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.382
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.223
GPT teacher head0.292
Teacher spread0.070 · 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.

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

Citations2
Published2011
Admission routes1
Has abstractyes

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