Bibliographic record
Abstract
It is to examine the part these studies played in the growth of the present high school curriculum that this thesis is written. One of the basic responsibilities of the educational system is that of providing a curriculum which keeps pace with the practical needs of the students, and the pressing demands for adaptability required in a democratic society. \nIt may come as a surprise to many to realize that there was no such thing as a general high school curriculum in Nova Scotia before 1885, and that only in the 1930’s did it take its present form. In the following pages the reader will be taken back to 1750, to see what efforts were made to provide youth with a worth-while education that would fit him for life. No attempt will be made to concentrate on any one subject, but rather, the curriculum as a whole will be examined over the years to the present day. \nThe first two chapters review the curriculum picture briefly in the United States and Canada, to supply background and precedent for many of the events and trends that helped form the program of studies in Nova Scotia. \nThe remaining four chapters concentrate on our own Province and its educational system and will, we trust, provide the reader with a sequential account of “The Development of the High School Curriculum in Nova Scotia.”
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".