Bibliographic record
Abstract
J. King Gordon's story is one of youthful vision and high ideals sustained throughout a life of concrete action at home and abroad. Grounded in his father's social gospel and given intellectual heft and hue by exposure to radical politics at Oxford and in New York, he returned to Canada as a self-described "Christian radical" and threw himself into the emerging social and political ferment of the 1930s. In Growing to One World, Eileen Janzen details a life spent championing progressive politics in Canada and a commitment to peace and diplomacy on the international stage. As a founding member of the League for Social Reconstruction, Gordon was one of the authors of the Regina Manifesto for the newly formed Co-operative Commonwealth Federation, the forerunner of today's NDP, and worked tirelessly on the party's behalf. Later, he realized his vocation as a member of the United Nations' division of human rights, serving in Korea, the Middle East, and the Congo as both an eyewitness to and participant in formative events shaping those regions. Exhaustively researched and informed by a sophisticated analytical grasp of political theory and international affairs, Growing to One World is a compelling look at an important supporter of peace, justice, and human rights across the globe.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".