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Enregistrement W2980305565 · doi:10.1353/vpr.2019.0039

Zooming In and Out: Theories of Poetry from Checking the Periodical Poetry Index

2019· article· en· W2980305565 sur OpenAlexvenueno aff
April Patrick

Notice bibliographique

RevueVictorian periodicals review · 2019
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueDigital Humanities and Scholarship
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPoetryIndex (typography)Search engine indexingScholarshipComputer scienceProcess (computing)ZoomRaw dataLiteratureInformation retrievalWorld Wide WebArtLawProgramming language

Résumé

récupéré en direct d'OpenAlex

Zooming In and Out:Theories of Poetry from Checking the Periodical Poetry Index April Patrick (bio) As the intermediary stage in the Periodical Poetry Index process, checking bridges the input of data through indexing and its output in encoding. Our earliest conceptions of this step assumed it would require simply editing citations for accuracy and correcting any typos from the data entry process; however, in practice, checking has evolved into an activity that requires rethinking assumptions about this process and about the nature of poetry as it was published in nineteenth-century periodicals. Indeed, this iterative approach to the checking portion of Periodical Poetry has illuminated, among other trends, a surprisingly common practice of publishing poems in groups. From the earliest stages of this project, we recognized the importance of reviewing the data collected through the indexing process, and after mere months into our work together we had devised a circular approach where we each checked the poems indexed by one of our collaborators. Our initial goal for this stage was to ensure each entry included the correct bibliographic details, something we believed essential to creating a high-quality digital index; thus, we called the stage "checking," as if we were students reviewing the answers on a peer's exam. Other terms used for this type of work include "editing," which comes with implicit connections to textual scholarship and scholarly editions of a work, and "data cleaning," which as David Mimno observes, problematically implies "that there is some kind of pure or clean data buried in a thin layer of non-clean data, and that one need only hose the dataset off to reveal the hard porcelain underneath the muck."1 Katie Rawson and Trevor Muñoz consider the vagueness of the phrase, lamenting that "the specifics of 'data cleaning' are not described anywhere but reside in the general professional practices, materials, personal histories, and tools of the researchers."2 In response, [End Page 618] they suggest this "obscuring language … should be a strong invitation to scrutinize, perhaps reimagine, and almost certainly rename this part of our practice."3 In our approach to this part of the workflow, we have recognized the incredible value of an iterative approach in which we return to the periodical, just like the indexer in the previous stage. What We Mean by Checking Because it is not as commonly used to denote this sort of work, the term "checking" allows us to define what this part of our process includes. According to the Oxford English Dictionary, checking is "to control (a statement, account, etc.) by some method of comparison; to compare one account, observation, entry, etc., with another, or with certified data, with the object of ensuring accuracy and authenticity."4 Indeed, the purpose of ensuring accuracy was our primary intention for checking, and with that in mind, the work of checking seemed the mundane part of our workflow, essentially scanning a spreadsheet of poems for errors and making small adjustments to commas in the first lines or correcting places where the poet's printed initials were transposed in indexing. In practice, however, the checking stage requires balancing both closer and more distant views of the data, not only looking at the page of the periodical to confirm the indexed entry is correct but also considering the trends and connections that appear across the larger collection of poems. In this stage we make sense of discoveries about our data. Throughout our various rounds of checking, we have always focused on correcting any minor errors from the indexing process. During the checking process, we also update entries based on changes to our data collection categories, such as poem length, which we adjusted after realizing we needed to account for very long poems over one hundred lines. For example, in 2014 we began rechecking items that had been checked in 2011, so the entries needed poet and signature gender, updates to the number of lines, and changes to the title fields. The multiple spreadsheets of poems indexed from the early decades of Blackwood's, 1817 to 1845, included 1,544 poems. To streamline the process of checking, the entries were consolidated into a master spreadsheet and sorted...

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,036
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesBibliométrie
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,993
Score d'incertitude au seuil0,039

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,036
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0070,005
Études des sciences et des technologies0,0070,056
Communication savante0,0120,031
Science ouverte0,0020,007
Intégrité de la recherche0,0040,007
Charge utile insuffisante (le modèle a refusé de juger)0,0080,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,021
Tête enseignante GPT0,245
Écart entre enseignants0,224 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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