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The Bio-Logos of Malta

2025· book-chapter· en· W4413185934 on OpenAlexaff
Randall Martin

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldPsychology
TopicScience Education and Perceptions
Canadian institutionsWestern University
Fundersnot available
KeywordsLogos Bible SoftwareComputer science

Abstract

fetched live from OpenAlex

Abstract This final chapter triangulates the drama of Paul’s shipwreck off Malta and three-month contact with the islanders (Acts 27–8) with William Strachey’s structurally derived report of the wreck of the Sea Venture on Bermuda as resources for Shakespeare’s creation of Prospero’s shipwrecks and his island encounter with Caliban. The latter’s environmental personhood, I argue, is the pre-colonial foundation of his linguistic and bodily resistance to Prospero and Miranda’s ‘salvaging’ programme of Humanist re-education. I open these intertextual connections by analysing a visual narrative of Paul’s Maltese shipwreck in Abraham Ortelius’s map of his Mediterranean journeys. I then explore how Paul’s encounters with the native Maltese provided him and his company with life-saving hospitality. But uniquely in the miracle narrative of Acts, the Maltese are not converted. Similarly under-examined in Strachey’s report are his detailed observations of Bermuda’s biodiversity. They became a resource for Shakespeare’s biogeographical conception of Caliban’s island, and in turn for Caliban’s spontaneously humane hospitality to the Italian castaways, which Prospero and Miranda later betray with colonial enslavement. After Prospero becomes conscious of the anarchic passions of revenge, he seems partly to acknowledge Caliban’s ‘salvaging’ bio-spirituality, as well as the ‘darkness’ of trying to extinguish it, in his divided Epilogue. I conclude by briefly speculating about Caliban’s ‘hereafters’ as a racialized slave or servant in mainland Europe.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.106
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0130.010
Scholarly communication0.0090.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0230.003

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 head0.066
GPT teacher head0.385
Teacher spread0.319 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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