A critical appraisal of Alvin Plantinga on justification and warrant
Bibliographic record
Abstract
In this thesis, I argue that even if Alvin Plantinga's externalist theory of warrant is essentially correct, internalism with respect to epistemic justification should not be abandoned. I argue that Internalist justification, understood in purely evidentialist terms, is both necessary for warrant, and desirable for the pragmatic benefits that it affords. Plantinga defines warrant as the quality or quantity, enough of which is both necessary and sufficient for turning true belief into knowledge. His theory states that a belief is warranted if it is produced by a reliable, truth-directed cognitive faculty functioning properly in an appropriate epistemic environment. In principle, it is not possible for a cognizer to know whether or not a given belief has warrant, since many of the relevant facts regarding the functioning of one's faculties and the congeniality of the epistemic environment are not the kinds of facts to which the cognizer has direct epistemic access. Internalist theories of epistemic justification hold that the factors that confer epistemic justification are internal to the mind, and at least potentially accessible to the cognizer upon reflection or introspection. I argue that a belief is justified if and only if it fits one's evidence. I also argue that it is plausible to conclude that beliefs that fail to be justified also lack warrant. If this is correct, then internalist justification, understood in evidentialist terms, affords the pragmatic benefit of providing an accessible criterion for assessing the epistemic status of a significant class of beliefs with respect to their warrant.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.026 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".