Marie Stopes and the Fern Ledges of Saint John, New Brunswick
Bibliographic record
Abstract
Abstract Marie Stopes (1880–1958) is best known for her controversial writings on sex, marriage and birth control, but during her 20s and 30s she carved out a successful career as a palaeobotanist. Here, we discuss her work on the Fern Ledges of Saint John, New Brunswick. The age of these fossil beds had long been shrouded in controversy. The eminent 19th-century geologist, Sir William Dawson, had argued that they were Devonian and represented remains of the oldest known terrestrial ecosystem. In 1910, Stopes was commissioned by the Geological Survey of Canada to reassess the taxonomy and age of this fossil flora. We provide the first detailed chronology of this 18-month long research project and highlight some of the most important aspects of the study. Her outstanding monograph, characterized by precise observation and interpretation, cut through decades of muddled thinking to prove that the beds were, in fact, Pennsylvanian. In addition, her palaeoecological inferences were well ahead of their time and also had biostratigraphical implications. Although she continued to intermittently publish geological works until the mid-1930s, the Fern Ledges project, which coincided with her disastrous first marriage to Reginald Gates, marked the beginning of the end of her palaeobotanical career and the start of her more extraordinary and enduring contribution to society.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".