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Record W4226336902 · doi:10.1108/jices-12-2021-0125

Critical care for the early web: ethical digital methods for archived youth data

2022· article· en· W4226336902 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

VenueJournal of Information Communication and Ethics in Society · 2022
Typearticle
Languageen
FieldComputer Science
TopicWeb Data Mining and Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFraming (construction)Context (archaeology)OriginalityIndigenousWorld Wide WebSociologyComputer scienceEngineeringHistorySocial scienceQualitative research

Abstract

fetched live from OpenAlex

Purpose This paper aims to provide a brief overview of the ethical challenges facing researchers engaging with web archival materials and demonstrates a framework and method for conducting research with historical web data created by young people. Design/methodology/approach This paper’s methodology is informed by the conceptual framing of data materials in research on the “right to be forgotten” (Crossen-White, 2015; GDPR, 2018; Tsesis, 2014), data afterlives (Agostinho, 2019; Stevenson and Gehl, 2019; Sutherland, 2017), indigenous data sovereignty and governance (Wemigwans, 2018) and feminist ethics of care (Cifor et al. , 2019; Cowan, 2020; Franzke et al. , 2020; Luka and Millette, 2018). It demonstrates a new method called an archive promenade, which builds on the walkthrough and scroll-back methods (Light et al. , 2018; Robards and Lincoln, 2017). Findings The archive promenades demonstrate how individual attachments to digital traces vary and are often unpredictable, which necessitates further steps to ensure that privacy and data sovereignty are maintained through research with web archives. Originality/value This paper demonstrates how the archive promenade methodological intervention can lead to better practices of care with sensitive web materials and brings together previous work on ethical fabrications (Markham, 2012), speculation (Luka and Millette, 2018) and thick context (Marzullo et al. , 2018), to yield new insights for research on the experiences of growing up online.

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)0.008
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.753
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0000.002
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 head0.163
GPT teacher head0.447
Teacher spread0.284 · 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