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Record W4225014877 · doi:10.1145/3491102.3501845

Unofficial Proxies: How Close Others Help Older Adults with Banking

2022· article· en· W4225014877 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCHI Conference on Human Factors in Computing Systems · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsModalitiesInternet privacyOlder peoplePsychologyBusinessComputer scienceGerontologyMedicineSociology

Abstract

fetched live from OpenAlex

We present results of a survey (n=42) investigating how close others (family members, friends, or other community members) assist older adults with banking tasks in Canada. We asked what types of banking tasks they help with and what modalities they used. Our results show many close others help older adults by leveraging online banking, and this is especially true when the close other is an older adult themselves. We also found that close others who help older adults via online banking often know the online banking credentials for the older adults they assist, which presents privacy and security issues and could open the door to financial exploitation. Our results demonstrate the need for the design of online banking mechanisms that more explicitly acknowledge the nuanced and temporally changing role of close others in helping older adults with banking.

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.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
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 head0.053
GPT teacher head0.309
Teacher spread0.256 · 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