Building an historical GIS platform from archival data
Bibliographic record
Abstract
We describe our efforts to create an Historical GIS platform for genealogical data in Nova Scotia. To build a demonstrable prototype, we use historical data from two communities, the "Old North End" of Halifax, and "Durham Village" in Pictou County. With the initial time set at 1881, these communities are considerably different in character on the urban/rural axis, by occupation, ethnicity, religion, and household composition. The data we have been compiling include (a) household-level geographic coordinates, (b) 1881 directory and census data, and (c) photographic images. The full-scale platform will utilize the archival records and output of the various community-based historical and genealogical groups around the province. We have conducted several sub-projects to develop the programming for joining arbitrary data from disparate research groups, and will report on how this approach can be used "to connect content and UX design practices to local contexts/local communities."
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".