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Record W4382133664 · doi:10.5430/wjel.v13n6p499

Highlighting Ideas of Human Rights: A Review of American Intellectuals’ Classic Writings

2023· review· en· W4382133664 on OpenAlexvenueno aff
Nuriadi Nuriadi, Muh. Syahrul Qodri, Indah Kharisma

Bibliographic record

VenueWorld Journal of English Language · 2023
Typereview
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsnot available
FundersUniversitas Mataram
KeywordsHuman rightsGeorge (robot)PluralMulticulturalismReading (process)Perspective (graphical)American literatureLawSociologyEnvironmental ethicsArt historyClassicsPhilosophyHistoryPolitical scienceArtLiterature

Abstract

fetched live from OpenAlex

This article intends to review the ideas of human rights appearing in several American intellectuals’ classic writings from the Puritan era up to the modern era. It is a descriptive qualitative writing whose focus is on a literature review. In so doing, close reading is applied as a method and interdisciplinary perspective as its framework It is found that the ideas of human rights have spread as a public issue from the Puritan era until the modern era when proposed by many intellectuals, i.e., Anne Hutchinson, Roger Williams, Thomas Jefferson, Thomas Paine, John Adams, James Madison, Frederick Douglass, Martin Delany, George Fitzhugh, Abraham Lincoln, Sarah Grimke, Louisa McCord, Margaret Fuller, Betty Friedan, William Lloyd Garrison, and so forth. In response to many inhumane social conditions in the United States, human rights ideas arose.The ideas certainly support the establishment of the United States as a country. Consequently, this fact indicates that human rights ideas have persisted in the veins of the American nation over time, preserving it as the most plural and multicultural one in which all entities are welcome and acknowledged.

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)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0170.020
Science and technology studies0.0010.003
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.038
GPT teacher head0.373
Teacher spread0.335 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

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Same venueWorld Journal of English LanguageSame topicInternational Law and Human RightsFrench-language works237,207