Queering the Digital Divide: Contextualizing 2SLGBTQ+ Older Adults' Experiences with Accessing Remote Service Provisions in Ontario
Bibliographic record
Abstract
The COVID-19 pandemic reshaped Western societies' relationship with Information and Communication Technology (ICT). Stay-at-home mandates in Ontario increased many people’s everyone's reliance on technology to work, socialize, and access services. In Western societies that are dominated by digital technologies, digital exclusion can have detrimental impacts on an individual’s health and well-being (Seifert et al. “Perceived Exclusion” 6). Unlike populations under the age of 55, older adults who lack digital literacy skills or who are digitally disconnected become socially excluded from an entire virtual universe (Seifert et al. “Double Burden” e99). Digital citizenship scholarship focused on the general older adult population in North America indicates that they lack the skills or devices needed to fully utilize the Internet (Perrin and Atske, Nimrod 159, Quan-Haase et al. 206). I am concerned with how equity-deserving groups, like 2SLGBTQ+ older adults, encounter unique challenges with accessing and utilizing ICT. Through a mixed-method quantitative and qualitative online study, I aim to contextualize how 2SLGBTQ+ older adults' experiences with new technologies are similar or different from their heterosexual counterparts. This dissertation identifies and unpacks the struggles 2SLGBTQ+ older adults faced during the pandemic with using ICT to better understand how service providers could have addressed digital divide gaps amongst this population during and beyond stay-at-home mandates. Exploring the intersections of queerness, aging, and technology and putting them into conversation with digital divide scholarship offered a nuanced look at how the internet is utilized by 2SLGBTQ+ older adults. This study explored the challenges rainbow seniors experienced with accessing social service provisions during the pandemic. Using participatory action research, I collaborated with 2SLGBTQ+ organizational leaders and activists to develop a comprehensive needs assessment that aimed to understand how rainbow seniors’ experiences with the internet differ from those of their heterosexual counterparts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".