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Record W2219148129

The Case and the Exceptions: Creating Instrumental Texts in Law and Literature

2009· article· en· W2219148129 on OpenAlexaff
Simon Stern

Bibliographic record

VenueTSpace · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicComparative and International Law Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCLARITYReading (process)Presentation (obstetrics)Legal writingFunction (biology)Index (typography)LawHistorySociologyLiteratureComputer scienceArtPolitical scienceLegal researchWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

In early 18th century England, the legal treatise was a young genre (some would say a nonexistent genre). Legal treatises are instrumental books, meant to be usable by the reader who consults a few pages rather than reading the whole book (and to be capable of steering the reader directly to those pages), and meant to be used as fodder for briefs and oral arguments. They are meant to produce more writing, and they are designed with that goal in mind. The changing format of 18th century legal treatises shows how they adapted themselves to these instrumental uses. Cross-referencing was already a familiar feature of law books, but the back-of-the book index underwent significant change during the 18th century. Changes in these books show how their creators came to understand the channeling function of indexes, which can help to frame the question for the reader, rather than serving only those readers who know in advance how the question must be framed. By the end of the eighteenth century, these books had begun to include multi-level indexes that allowed for orderly, visual, telegraphic presentation of doctrinal distinctions. Just as treatises, by rationalizing the basic principles and structure of an area of law, may have helped to facilitate further doctrinal clarity, thoroughness, and specificity, the increasingly effective channeling function of indexes may have played a small part in encouraging lawyers to expect that fine distinctions can be captured quickly and precisely. These developments were occurring at the same time that the literary marketplace in England was beginning to include books designed for professional writers, such as rhyming dictionaries, thesauruses, and collections of quotations. A comparison between the indexes in law books, and those in books for writers, helps to identify the pragmatic needs of professionals in each area.

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)0.012
metaresearch head score (Gemma)0.024
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 score0.029
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0100.033
Scholarly communication0.0290.029
Open science0.0030.022
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0100.003

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 head0.022
GPT teacher head0.372
Teacher spread0.351 · 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
Published2009
Admission routes1
Has abstractyes

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