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Record W7027391875

Concealing and Revealing: Information Design to Strengthen Civic Literacy in an Age of Digital Communication

2021· dissertation· en· W7027391875 on OpenAlexaboutno aff

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2021
Typedissertation
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsFraming (construction)Digital mediaCitizenshipPoliticsDemocracySemioticsDigital literacyMedia literacyPower (physics)
DOInot available

Abstract

fetched live from OpenAlex

This thesis work responds to emerging issues in media and civic awareness in Canada, exploring how design can be used to highlight, examine and expose characteristics of the digital space in order to enhance young citizens’ media literacy. As the opening chapters will establish, younger Canadians are experiencing a unique combination of factors that render them insufficiently prepared to participate as digital citizens. These issues are compounded by digital threats to democratic values such as the rise in manipulative or propagandistic content, as well as intellectual silos created by algorithmic filtering. The title of the thesis, “concealing and revealing” speaks to our relationship with the digital space that is all at once present, immediate and yet, invisible, and elusive. My creative work aims to illuminate the invisible power dynamics perpetuated by digital tools using information design and data visualizations, presented through a large sculptural installation and a series of illustrated notebooks. The projects’ research focuses on teens and young adults, but the outcomes provide information that is pertinent to citizens of all ages. The projects rely on critical discourse analysis, semiotics and practice-led approaches to research. The theoretical framing of the projects apply Marshall McLuhan’s media theories to explore how we as a society may begin to evaluate our political experience in the digital age, in order to better understand the lasting impacts on citizenship and liberal democracy.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.006
Open science0.0010.000
Research integrity0.0000.001
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 head0.110
GPT teacher head0.324
Teacher spread0.215 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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