Collateral damage. Personal lenders and the creation of national mortgage markets in North America, 1890s-1960s
Bibliographic record
Abstract
Between the 1880s and 1950s, national mortgage markets were created in the United States and Canada. The formative role of institutions and federal governments are well understood. Personal (individual or ‘private’) lenders have been omitted from the narrative although, in the late 1940s, they still provided a quarter of residential mortgages in the United States and two fifths in Canada. Rarely targeted, they were collateral damage, especially, of state initiatives. The distinctive nature of mortgages, secured on real estate, made the creation of national markets difficult. The character of personal loans – local, non-standard, non-amortized, and often informal -- made their assimilation into any supra-local market especially challenging. Their significance declined in waves: the 1900s, 1920s, and then, under government influence, after 1945. They persist in the reduced gaps left by institutions. We should pay them more attention.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".