MétaCan
Menu
Back to cohort
Record W2074957214 · doi:10.1177/0014585814529223

Forging a linguistic identity in the age of the Internet

2014· article· en· W2074957214 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueForum Italicum A Journal of Italian Studies · 2014
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIdentity (music)The InternetFace (sociological concept)ModalitiesLinguisticsComputer-mediated communicationInstant messagingPsychologySociologyCommunicationMedia studiesComputer scienceArtAestheticsWorld Wide WebAnthropology

Abstract

fetched live from OpenAlex

Today, computer-mediated communication (CMC) has made written communication a prevalent form of daily interaction through e-mails, Facebook, Twitter, text messages and the like. As a consequence, languages (written and spoken) seem to be shaped more and more by the modalities of digital media and of an ‘instant communication response’ culture. Linguistic identity, or the use of language to portray oneself as part of a community, is being shaped as well by the same modalities. Traditionally, the way individuals and communities used specific forms of language in face-to-face (F2F) situations shaped perceptions of identity (personal and communal). Now, the question can be asked: Are these changing in the age of the Internet, when CMC has extended the concept of community in a global way? This article will look at this question as it concerns linguistic identity in Italy, assessing its implications in the light of the traditional sociolinguistic study of language as a conveyor of identity.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0020.001
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 head0.028
GPT teacher head0.312
Teacher spread0.283 · 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