Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Exception handlers—and effect handlers more generally—are language mechanisms for structured nonlocal control flow. A recent trend in language-design research has introduced lexically scoped handlers, which address a modularity problem with dynamic scoping. While dynamically scoped handlers allow zero-overhead implementations when no effects are raised, existing implementations of lexically scoped handlers require programs to pay a cost just for having handlers in the lexical context. In this paper, we present a novel approach to implementing lexically scoped handlers of exceptional effects. It satisfies the zero-overhead principle—a property otherwise met by most modern compilers supporting dynamically scoped exception handlers. The key idea is a type-directed translation that emits information indicating how handlers come into the lexical context. This information guides the runtime in walking the stack to locate the right handler. Crucially, no reified lexical identifiers of handlers are needed, and mainline code is not slowed down by the presence of handlers in the program text. We formalize the essential aspects of this compilation scheme and prove it correct. We integrate our approach into the Lexa language, allowing the compilation strategy to be customized for each declared effect based on its expected invocation rate. Empirical results suggest that the new Lexa compiler reduces run-time overhead in low-effect or no-effect scenarios while preserving competitive performance for effect-heavy workloads.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it