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Record W4307127168 · doi:10.1353/ecs.2022.0056

Reinstating Restoration

2022· article· en· W4307127168 on OpenAlexaff
Ramesh Mallipeddi

Bibliographic record

VenueEighteenth-Century Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOpposition (politics)RestructuringPeriodizationConventionPolitical scienceHistoryNominationStatus quoLawPolitics

Abstract

fetched live from OpenAlex

In 2013, the Modern Language Association (MLA) circulated a draft proposal to restructure existing "divisions" and "discussion groups," in an effort to respond to intellectual shifts in the new millennium.The MLA working group's plans for revising the divisional structure included the consolidation of traditional periods, and the addition of new subfields in emerging areas.Among the proposed changes was the amalgamation of the divisions on "Restoration and Early-Eighteenth-Century English Literature" and "Late-Eighteenth-Century English Literature" into a single forum on the "Long Eighteenth Century."Opposition to the move from the eighteenth-century scholarly community was swift and unanimous.When MLA invited comments on the initiative as part of their review process, more than eighty members-graduate students, early career and senior scholars, including four past presidents of ASECS, and several current and former board members of this journal-weighed in, urging the organization not to act on the proposed merger because such rearrangement would, if implemented, not only reduce the number of guaranteed panels at the annual convention, but also excise the Restoration as a literary historical category altogether.While acknowledging the limitations inherent to periodization and noting that divides between periods seldom correspond to divides between centuries, the concerned members nevertheless made reasoned, eloquent, and conscientious appeals for preserving the Restoration as a separate entity, owing to its rich literary output and its importance for understanding the broader contours of the field. 1 In response to this groundswell of opposition, MLA maintained the status quo and retained the two-forum structure.

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)0.028
metaresearch head score (Gemma)0.039
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: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.039
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0120.024
Scholarly communication0.0130.017
Open science0.0030.023
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0110.003

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 head0.057
GPT teacher head0.263
Teacher spread0.206 · 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
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
Published2022
Admission routes1
Has abstractyes

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