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Record W3165898262 · doi:10.1177/17506980211010694

Digital disorientation and place

2021· article· en· W3165898262 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

VenueMemory Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSense of placeAestheticsPoliticsSociologyAffect (linguistics)Everyday lifeEpistemologySocial psychologyMedia studiesPsychologyLawPolitical scienceSocial scienceCommunicationPhilosophy

Abstract

fetched live from OpenAlex

Digital technologies affect experiences of place in ways that are disorienting because they overwhelm us with information and images, bring into question what is real and what is fake, confuse real and virtual reality, and exacerbate extreme views about who belongs where. The consequences of this ‘digital disorientation’ might seem to be experienced as unremarkable and benign. However, it is becoming increasingly clear that these consequences include a digitally poisoned sense of place based on exclusionary attitudes paradoxically fostered in the echo chambers of non-place communities. Resisting this and its political manifestations will require finding ways to promote an open and inclusive digital sense of place that is necessarily grounded in the actual places of everyday life; that understands that digitally these actual places are both permeated by and reach out into distant times and places; and that embraces rather than denies difference.

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)0.000
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 score0.226
Threshold uncertainty score0.218

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.051
GPT teacher head0.367
Teacher spread0.316 · 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