Determinants of Bank Closures: Exploring the Relationship between Neighborhood Characteristics and Bank Branch Locations
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
Retail Banking in Canada has experienced significant changes perpetuated by both digital trends in retail and changes in consumer demand. These changes have resulted in significant decreases in client interactions with physical branches in favor of digital platforms (online, mobile, phone banking). As the “Big Five” Canadian banks pursue network optimization strategies focused on reinvesting savings into their digital channels, branch closures will accelerate, resulting in market gaps. Thus, the central aim of this study is to understand the relationship between neighborhood characteristics (built environment and socio-economic) and bank branch locations. Using the city of Toronto as a case study, this research addresses three objectives: (i) to identify neighborhoods underserviced by the “Big Five” Canadian banks; (ii) to examine the spatial relationship between neighborhood characteristics and branch locations; and (iii) to quantify the key neighborhood characteristics linked to branch locations. This study finds that financial exclusion continues to be associated with local dynamics of physical topography, road network, demographics, and socio-economic status. While financial exclusion is becoming a growing area of concern for policy makers, this research finds that access to affordable financial services still proves to be an issue that requires attention.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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