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Record W3153877322 · doi:10.5539/ijel.v11n3p39

A Rhetorical Approach to Critical Reading of Literary Texts

2021· article· en· W3153877322 on OpenAlexvenueno aff
Hong Zhang

Bibliographic record

VenueInternational Journal of English Linguistics · 2021
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
Fundersnot available
KeywordsRhetorical questionReading (process)Interpretation (philosophy)PersuasionRhetorical deviceRhetorical modesConstructiveMeaning (existential)SociologyLinguisticsLiteratureEpistemologyArtPhilosophyComputer scienceProcess (computing)

Abstract

fetched live from OpenAlex

From a rhetorical point of view, reading is not an isolated process of absorbing the meaning of words in a text but a creative activity in which the reader constructs meaning through the symbolic exchange with the text in a particular situation. This study elaborates on the rhetorical features of literary texts through the lens of rhetorical situation, rhetorical purpose, and Aristotle’s three means of persuasion. It then illustrates how to approach a literary text rhetorically through the interpretation of Sandra Cisneros’ The House on Mango Street, shedding light on the development of critical reading in literary instruction. The study displays the literary text’s rhetoricity and demonstrates that the rhetorical approach enables the readers to explore the persuasive mechanism of a literary text, examine the sources the writer marshals to adapt to the audience and make their judgments based on the ethical, emotional, and logical proofs. Furthermore, the rhetorical approach to literary reading provides theoretical ground for a rhetorical mode of literary instruction, which directs our focus on the readers’ constructive role and creates more space for individual interpretation. In this way, a rhetorical approach to literary reading plays a significant role in developing student readers’ creativity, critical thinking, and rhetorical awareness both in reading and writing.

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)0.195
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.905
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.195
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)0.0000.000

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 head0.065
GPT teacher head0.424
Teacher spread0.359 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

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