Eyeing ID: Access to Identification as a Barrier to Banking and Other Social Determinants of Health
Bibliographic record
Abstract
Personal identification (ID) is a prerequisite to many financial and social services; however, many vulnerable residents do not have ID and lack the resources to acquire it. To assess the impact of ID inaccessibility in a local context, a study was conducted throughout New Brunswick, Canada. The study objective was to understand the implications of ID requirements and the barriers to acquiring it through the lens of consumers. This mixed-methods, observational study included surveys and interviews. The survey collected demographics, socioeconomic status (SES), financial behaviors and experiences, and barriers to accessing ID. The semi-structured interviews explored individual experiences. In order to address disparities in health and social outcomes, ID requirements and barriers to access need to be acknowledged and mitigated. A total of 142 surveys were completed. Many respondents reported difficulty obtaining or replacing a driver's license (30.8%), a provincial photo ID (47.7%), or their birth certificate (39.4%), identifying cost (34.4%) and required documentation (28.1%) as the main barriers. Thematic analysis identified three main themes: the difficulty of living without ID, barriers to obtaining or replacing an ID, and an exploration of solutions. Current ID policies restrict access to community services such as banking, housing, and employment, which are intended to support individuals to improve their situation and gain autonomy. Policies and services are required to address this urgent issue.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".