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Record W2999802691 · doi:10.3968/11462

Literary Discourse and Human Rights in Martin Luther King’s Speech: ‘I Have a Dream.’

2019· article· en· W2999802691 on OpenAlexvenueno aff
Mujahid Ahmed Mohammed Alwaqaa

Bibliographic record

VenueStudies in literature and language · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDestiny (ISS module)Human rightsPower (physics)DreamSociologyMoresLiterary criticismLawAestheticsLiteraturePoliticsPhilosophyPolitical sciencePsychologyLinguistics

Abstract

fetched live from OpenAlex

This paper attempts to explore the role of literary discourse, particularly engaged literature, in consolidating the values of human rights. It is an in-depth literary analysis of Martin Luther King’s speech: “I Have a Dream” in terms of form and content. Central to this paper is an effort to find out the tremendous power of literary discourse in positively changing and shaping individuals and societies by creating public awareness regarding rights and duties. Burning issues such as human rights violations and abuses are often brought into awareness and directly tackled by literary discourse. When people are given their rights, social justice and human development become inevitable. Findings from the discussion and analysis of Martin Luther King’s speech “I Have a Dream” show that literature do have a pivotal role to play in human rights promotion and social development. This role is important because literature does not exist for its own sake or in a vacuum. It is, rather, a true reflection and mirror of the mores and milieu of society. Moreover; it is a powerful expression of the sufferings, agonies and above all aspirations of the masses. The ability of human beings to articulate themselves in the form of literary discourse is the most substantial power they possess in shaping their destiny and life in general.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.474

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)0.0000.000

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 head0.025
GPT teacher head0.317
Teacher spread0.292 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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