Bibliographic record
Abstract
This thesis examines the causal explanation in molecular biology, particularly focusing on the predominant explanatory account in biology, namely, the new mechanistic account. According to this account, a phenomenon is explained by a mechanism, that is, a causal structure with a specific organization of entities and activities responsible for the phenomenon in question. For example, consider the mechanism of protein synthesis. It consists of entities (e.g., DNA) and activities (e.g., transcription) that are responsible for synthesizing proteins, that is, influencing the phenotypic traits of an organism. The thesis aims to further advance this debate by emphasizing three points. Firstly, it aims to structure and present the debate on the issue, particularly by focusing on the background concepts related to the new mechanistic account, such as: causation, explanation, mechanism, biological functions, and law of nature. In particular, it outlines the interventionist and production accounts of causal explanation, the causal role account of biological functions, and the mechanistic approach to laws of nature. Secondly, it presents various characterizations of the new mechanistic account, advocating for a consensus view on the concept of a mechanism. Additionally, it emphasizes alternative causal-explanatory structures, such as causal pathways and cascades. For each of these three structures, the thesis outlines their respective aspects regarding their corresponding explanation processes, namely the ontic, epistemic, and strategic aspects. The thesis argues that mechanisms, along with the aforementioned structures, are distinct in the strategic and epistemic aspects, while sharing certain features in the ontic aspect, asserting that mechanisms are the explanatory privileged causal structure. Thirdly, it aims to apply the interventionist account of causal explanation and the three aspects of mechanisms and pathways outlined above to two case studies from scientific practice, namely: (i) the intervention in the glycolytic pathway to prevent the growth of cancer cells, and (ii) the characterization of natural selection in terms of causal-explanatory structures. Regarding (i), the thesis argues that both the pathway’s epistemic aspect and the interventionist account can serve as useful conceptual frameworks. As for (ii), the thesis introduces a novel perspective, contending that natural selection could be partially characterized as a pathway.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.025 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".