Bibliographic record
Abstract
This article concerns the US half of the Canadian-US relationship in the medium future. Issues of focus include demographic and economic changes in the two countries and how the Trump presidential candidacy, aided in large part by consultant and former White House chief strategist Steve Bannon, tried to frame both negatively with respect to the US' history of a fairly open economy. Within the next 25 years, the United States, like most of the Organisation for Economic Co-operation and Development (OECD), will continue to have better job growth in the service industries than in manufacturing ones, necessitating an acknowledgement by both the public and private sectors that significant jobs retraining is necessary. In regard to Canada, this article argues that what is needed is more of a “tweak” to NAFTA, to recognize increased automation and include items like new computerized auto parts not covered in the original agreement, rather than a complete overhaul of the agreement. Canada and the US will still be talking to each other in 25 years' time.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.041 | 0.024 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 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".