From digital access to social inclusion : an investigation into the supportive role of service organizations on people experiencing homelessness
Bibliographic record
Abstract
Access to information and communication technologies (ICTs) has evolved from luxury to necessity, profoundly impacting social inclusion. While many people experiencing homelessness (PEH) possess mobile phones, various challenges hinder their ability to fully benefit from ICT resources. Social support —instrumental, emotional, and informational from social and public service organizations is essential in bridging this divide. This research aims to (i) identify the social support gaps; (ii) examine the digital and social inclusion status of PEH in British Columbia (BC), Canada; (iii) develop a conceptual framework for the impact of social support from organizations on the digital and social inclusion of PEH; (iv) identify the impact of various types of support on promoting digital and social inclusion; and (v) investigate the mediation effect of digital inclusion. Using a mixed-methods approach, data were collected from 87 staff members of organizations and 229 PEH in BC. Qualitative data were analyzed using thematic analysis, and quantitative data were examined using Partial Least Squares-Structural Equation Modeling (PLS-SEM) based on the conceptual framework and hypotheses developed. Findings reveal significant gaps in instrumental, emotional, and informational support, exacerbated by personal barriers (e.g., safety concerns, low digital literacy, affordability, health challenges), organizational challenges (e.g., inadequate staffing, spatial and financial constraints, limited operating hours, policy constraints, and misunderstandings between staff and PEH), and difficulties PEH face in accessing information about available services, navigation and mobility challenges, and societal stigma. This research presents and validates a framework showing how social support from service organizations affects the digital and social inclusion of PEH. Supported by PLS-SEM, the research finds that instrumental and informational support directly enhanced both digital and social inclusion, while emotional support primarily influenced social inclusion indirectly through digital inclusion. The research also emphasized the mediating role of digital inclusion between social support and social inclusion. iv In summary, this research extends the social support theory within the context of digital equity, providing a comprehensive hybrid database and proven methodology for research involving PEH. The validated conceptual model offers valuable insights for policymakers and service organizations to formulate comprehensive support strategies to help PEH achieve digital and broader social inclusion.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".