Bibliographic record
Abstract
Dr. J. W. Grant MacEwan, educator, environmentalist, politician and MacEwan University’s namesake once said… …about the planet “Thou shalt love and cherish the Great World of Nature, God’s House on loan to us for a season. Conscientious tenants should aspire to nothing less the lofty, practical and moral roles of caretakership. Good citizens should be grateful for the privilege and honor of answering to the challenge of those roles commonly known as conservation and environmental protection.” …about the people “Thou shalt despise the sins of extravagance and waste in the lives of both individuals and nations. In a world with limited resources and soaring populations, both breed hunger and misery.” …and, about profits… “Consider well thy regard for money. In the lives of young people, exercises in making and saving money may be good but when wealth becomes a object of worship for wealth’s sake or is accumulated in greedy and dishonest ways, there is not much to be said for it and there are many better shapes for a lifetime purpose. ” Although these assertions were made more than 40 years ago, they could not be more contemporary.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.373 | 0.250 |
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".