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Record W4390342283 · doi:10.29173/jjs120

The Letters of John H. Crowder

2023· article· en· W4390342283 on OpenAlexvenueno aff
Audrey Gibson

Bibliographic record

VenueJournal of Juvenilia Studies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature: history, themes, analysis
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryComputer science

Abstract

fetched live from OpenAlex

In the midst of the American Civil War, sixteen-year-old John H. Crowder, a free person of color, penned a series of letters that offer insight into the experiences, hopes, obstacles, and discrimination faced by young African Americans during the nineteenth century. Serving in the Louisiana Native Guard, one of the Union’s pioneering regiments that welcomed people of color, Crowder writes to declare his youthful ambitions and his unwavering resilience against his often disapproving superior officers. Additionally, within these letters Crowder’s profound love for his mother and a female friend is revealed, along with his determination to secure a stable future for the women in his life. The preservation of Crowder’s letters, alongside the story of his mother's pursuit of a military pension after Crowder’s death, brings to light the oft-overlooked contributions and experiences of African Americans in the post-Antebellum South. In this “Spotlight on Juvenilia,” I delve into the story behind the preservation of Crowder’s letters, exploring the unique challenges and triumphs experienced by young African Americans, as well as their significant role in shaping the Civil War narrative. Moreover, I emphasize the importance of amplifying diverse historical perspectives, particularly those of youth and people of color. By shedding light on the interplay between personal agency and societal constraints for Crowder, this exploration underscores the significance of his community’s voices in reshaping historical discourses and highlights the far-reaching implications of their experiences during this pivotal period in history.

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)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.045
GPT teacher head0.270
Teacher spread0.225 · 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
Published2023
Admission routes1
Has abstractyes

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