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Record W388167214

Which Tongue To Speak With? Philippine Poetry and the Nature of Language

2010· article· en· W388167214 on OpenAlexvenueno aff
Meredith Ramirez Talusan

Bibliographic record

VenuePostcolonial text · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicPhilippine History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryLinguisticsSubalternIndigenousFirst languageSociologyOpposition (politics)ColonialismTagalogLiterary languageHistoryLiteratureArtPhilosophyPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

In attempting to examine and imagine the intertwined relationship between language, literature, and community, the Philippines provides an illuminating case because it is one of the few countries in the world where books are published in both an indigenous and a colonial language at comparable rates. This paper examines the work of one poet, Cirilo F. Bautista, because not only is he one of the leading figures in contemporary Philippine poetry, but he has established his reputation by writing in both his native Tagalog and borrowed English. The paper questions these oppositions of nativeness and foreignness along both linguistic and cultural lines. By focusing on two of Bautista's works, Boneyard Breaking and Sugat ng Salita (Wounds of Words), collections of lyric poems written at around the same time, the paper shows how language affects literary production and perceptions of community. Specifically, this paper demonstrates that a native language has the ability to imagine a community outside its own boundaries at both a thematic and a linguistic level, thereby questioning the opposition between native and foreign, as well as a metaphoric that places native language in close proximity to a biological function. For Bautista, it is precisely the combination of an appeal to the commonality of biological observation and strategic use of language that allows him to transcend the boundaries of a native/foreign dichotomy. However, this paper also argues that Bautista accomplishes this transcendence in more nuanced ways through Tagalog, and must thus also speculate on the conditions under which these nuances can become translatable to an English-speaking readership.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.939
Threshold uncertainty score0.965

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.267
Teacher spread0.263 · 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 designNot applicable
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
Published2010
Admission routes1
Has abstractyes

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