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Record W4405795487

PEDAGOGIES OF THE DATAFIED: MATERIAL FOUNDATIONS FOR LITERACIES OF THE SUBJECT IN THE 21ST CENTURY

2021· article· en· W4405795487 on OpenAlexaff
Michael Lithgow

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsAthabasca University
Fundersnot available
KeywordsSubject (documents)SociologyMathematics educationEpistemologyPedagogyPhilosophyPsychologyComputer scienceLibrary science
DOInot available

Abstract

fetched live from OpenAlex

What it means to be human, relevant and meaningful is no longer certain within emerging regimes where computational complexity and data analysis increasingly determine conditions of prosperity and authority. Preparing students for futures within this transforming landscape of emerging technologies and new patterns of social organization raises important issues of literacy, power and subjectivity alike. If the hailing mechanisms of the subject are largely modulated through digital and algorithmic protocols, what kinds of literacies might help expand individual and group influence over subject formation? Traditional approaches to digital literacy have tended to overlook techno-material aspects of network functionality, which risks diminishing the degree to which individuals and groups can extend influence over subject formation. This paper argues for an expanded approach to digital literacy that addresses the techno-material foundations and full range of computational protocols on which network societies depend. Learning to navigate and manipulate the material-discursive apparatus in network societies can help individuals and groups apperceive assemblages of biopower while expanding possibilities for shaping subjectivities in datafied contexts.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score1.000

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 communication0.0010.002
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.345
GPT teacher head0.537
Teacher spread0.192 · 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.

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

Citations2
Published2021
Admission routes1
Has abstractyes

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