Exploring Privilege in the Digital Divide: Implications for Theory, Policy, and Practice
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.
Bibliographic record
Abstract
Background and Objectives: The digital revolution has resulted in innovative solutions and technologies that can support the well-being, independence, and health of seniors. Yet, the notion of the "digital divide" presents significant inequities in terms of who accesses and benefits from the digital landscape. To better understand the social and structural inequities of the digital divide, a realist synthesis was conducted to inform theoretical understandings of information and communication technologies (ICTs); to understand the practicalities of access and use inequities; to uncover practices that facilitate digital literacy and participation; and to recommend policies to mitigate the digital divide. Research Design and Methods: A systematic search yielded 55 articles published between 2006 and 2016. Synthesis of existing knowledge, combined with user-experience elicited through a deliberative dialogue session with community stakeholders (n = 35), made visible a pattern of privilege that determined individual agency in ICT access and use. Results: Though age is consistently centralized as the key determinant of the digital divide, our analyses, which encompassed both van Dijk's resources and appropriation theory and intersectionality, appraised this notion and revealed that age is not the sole determinant. Findings highlight the role of other factors that contribute to digital inequity among community-dwelling middle-aged (45-64) and older (65+) adults, including education, income, gender, and generational status. Discussion and Implications: Informed by results of a realist synthesis that was guided by intersectional perspectives, a conceptual framework was developed outlining implications for theory, policy, and practice to address the wicked problem that is the digital divide.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it