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Record W4405852275 · doi:10.47135/mahabbah.v4i1.78

IMPACT OF ERASMUS, MARTIN LUTHER, AND MICHELANGELO AS CULTURAL CHANGE AGENTS DURING THE RENAISSANCE PERIOD

2023· article· en· W4405852275 on OpenAlexaff
Joshua S. Hopping, Yusak Tanasyah

Bibliographic record

VenueMAHABBAH Journal of Religion and Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCultural and Artistic Studies
Canadian institutionsSt. Stephen's University
Fundersnot available
KeywordsErasmus+Period (music)The RenaissanceHistoryArtArt historyClassicsAesthetics

Abstract

fetched live from OpenAlex

This study discusses three cultural change agents: Erasmus, Martin Luther, and Michelangelo. Each of these figures played a significant role in shaping the cultural landscape of their time, and their influence can still be felt today. Erasmus was a Dutch Renaissance humanist who promoted a return to classical learning and scholarship. His writings, which were critical of the established church, helped pave the way for the Protestant Reformation. Erasmus also advocated for the use of the vernacular in religious texts, making them more accessible to ordinary people. Martin Luther was a German theologian and monk who is best known for his role in the Protestant Reformation. Luther's ideas challenged the authority of the Catholic Church and led to the establishment of new Protestant denominations. Luther's translation of the Bible into German helped make religious texts more accessible to a wider audience. Michelangelo was an Italian Renaissance artist who made significant contributions to the fields of painting, sculpture, and architecture. His works, including the ceiling of the Sistine Chapel and the sculpture of David, are considered masterpieces of Western art. Michelangelo's works helped redefine the possibilities of art and inspired future generations of artists. Together, Erasmus, Martin Luther, and Michelangelo represent a diverse set of cultural change agents who helped shape the course of Western culture. Their ideas and works continue to influence and inspire people today, reminding us of the enduring power of art, scholarship, and faith.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.245

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 head0.044
GPT teacher head0.372
Teacher spread0.328 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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