MétaCan
Menu
Back to cohort
Record W4401478919 · doi:10.16995/dscn.11062

Long Literary Covid: Archive of the Digital Present (ADP) and Reflections on the Meaning of Data About Pandemic Literary Events

2024· article· en· W4401478919 on OpenAlexaffvenueabout
Jason Camlot, Salena Wiener

Bibliographic record

VenueDigital Studies / Le champ numérique · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsSimon Fraser UniversityConcordia University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

How did the COVID-19 pandemic and its accompanying social restrictions and lockdowns impact literary activities and events across Canada? Out of this question developed the research project called “Archive of the Digital Present for Online Literary Performance in Canada (COVID-19 Pandemic Period),” or ADP for short—which entailed collecting data (information and audio-visual documentation) about pandemic literary events, and developing a searchable database designed to be used for reflection, study, and analysis of this unique period of literary history as it unfolded, largely on social media and virtual telecommunications platforms. This article focuses on the important and complex task of collecting data about pandemic literary events in Canada. We describe the processes of data collection and presentation and reflect on some of the possible meanings of data that arose through the process of attempting to structure information about ephemeral events gleaned through public digital platforms. As we describe the process of collecting, structuring, and curating data about pandemic literary events, we consider the import of affect and emotion in a disembodied, digital historical era, and what it means when events of literary expression and human encounter are born and continue to exist as digital data. We argue that data becomes an important locus of affective structures and textures of the pandemic by identifying some of the key generic forms that emerged through the affordances of online pandemic event platforms, and by theorizing some of the qualities of pandemic temporality and how they trouble attempts to conceptualize this period in literary historical terms. Quel a été l'impact de la pandémie de COVID-19 et des restrictions sociaux et verrouillages qui l'ont accompagnée sur les activités et événements littéraires à travers le Canada ? C'est à partir de cette question qu'est né le projet de recherche intitulé « Archive of the Digital Present for Online Literary Performance in Canada (COVID-19 Pandemic Period) », ou ADP en abrégé, qui consistait à collecter des données (informations et documentation audiovisuelle) sur les événements littéraires pandémiques et à développer une base de données consultable conçue pour être utilisée à des fins de réflexion, d'étude et d'analyse de cette période unique de l'histoire littéraire telle qu'elle s'est déroulée, en grande partie sur les médias sociaux et les plateformes de télécommunications virtuelles. Cet article se concentre sur la tâche importante et complexe de la collecte de données sur les événements littéraires pandémiques au Canada. Nous décrivons les processus de collecte et de présentation des données et réfléchissons à certaines des significations possibles des données qui sont apparues au cours du processus de structuration des informations sur les événements éphémères glanés sur les plateformes numériques publiques. En décrivant le processus de collecte, de structuration et de conservation des données sur les événements littéraires pandémiques, nous examinons l'importance de l'affect et de l'émotion dans une ère historique numérique désincarnée, et ce que cela signifie lorsque des événements d'expression littéraire et de rencontre humaine naissent et continuent d'exister en tant que données numériques. Nous soutenons que les données deviennent un lieu important de structures affectives et de textures de la pandémie en identifiant certaines des formes génériques clés qui ont émergé grâce aux possibilités des plateformes d'événements pandémiques en ligne, et en théorisant certaines des qualités de la temporalité pandémique et la façon dont elles troublent les tentatives de conceptualisation de cette période en termes d'histoire littéraire.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.136
GPT teacher head0.371
Teacher spread0.235 · 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 designQualitative
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
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueDigital Studies / Le champ numériqueSame topicIntellectual Property LawFrench-language works237,207