Bibliographic record
Abstract
Abstract The notion of causation that Mary Shepherd develops in her 1824 An Essay Upon the Relation of Cause and Effect (ERCE) has a number of surprising features that have only recently begun to be studied by scholars. This relation is synchronic, rather than diachronic (ERCE pp. 49–50); it always involves a ‘mixture’ of pre-existing objects (ERCE pp. 46–7); and the effect must be ‘a new nature, capable of exhibiting qualities varying from those of either of the objects unconjoined’ (ERCE p. 63). In this essay, I argue for an emergentist interpretation of Shepherd’s causal theory. On the reading I defend, all effects have qualities that metaphysically emerge from the complex interactions of their constituents. This reading explains the structure of Shepherd’s causal relation and clarifies the central aims of her philosophical project. In response to the problems raised by the science of her time, Shepherd developed a theory of emergence and published it during the period when the concept was first being shaped and adopted by prominent philosophers. Her work thus merits a place in the history of emergentist ideas.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".