Northern Exploration, Boundary Surveys, and Borderlands: Reports, Documents, and Maps from the United States Congressional
Bibliographic record
Abstract
Significant interdisciplinary scholarship exists concerning the unique economic, social, and political culture of international border and frontier areas. Notable themes of Alaskan and northern Canadian history also include discovery, exploration, and boundary issues. Primary literature concerning these topics is dispersed in many sources. One such source, the United States Congressional Serial Set , has been re-indexed and digitized, allowing online access to the full text documents and high-resolution images of the accompanying maps and illustrative material. This version, covering the years 1817–1980, was searched for citations pertaining to the discovery, exploration, and boundaries of Alaska and northern Canada. Summary level bibliographic records were reviewed for all entries, represented by thirty-three subject and geographic index terms (nineteen northern expeditions as listed under the broad category of Discovery and Exploration plus fourteen additional subject and geographic terms selected from the cross-references and related topics presented by the software). Numerical counts and examples of complete citations are provided. Results illustrate the usefulness of the digitized Serial Set , available to patrons of numerous US and Canadian libraries, in researching these topics in a quick and efficient manner. The set also provides additional opportunities for northern research. Many of the explorations and surveys contain historical scientific data and observations that are difficult to extract from modern sources. Viewing northern affairs broadly, the set concerns the entire northern US border areas and their historical, political, military, and diplomatic relations with Canada.
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.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.028 | 0.083 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".