Strickland-Lite: Padilla's Two-Tiered Duty for Noncitizens
Bibliographic record
Abstract
The quarter-century-old ineffective assistance of counsel framework announced in Strickland v. Washington recognizes a Sixth Amendment duty to investigate the law and facts underlying a criminal defendant’s legal predicament. In Padilla v. Kentucky the Supreme Court of the United States for the first time extended the Strickland analysis to cover the right of noncitizen defendants to receive information about the immigration consequences of a conviction. Faced with the competing considerations of providing noncitizen criminal defendants with critical information about immigration consequences, on the one hand, and the burden on defense attorneys of researching immigration law, on the other hand, this Article argues that the Court split the difference and invented a “Strickland-lite” duty. Under Strickland-lite, the Court failed to require that criminal defense attorneys investigate the law and facts relevant to immigration consequences as fully as it has long required attorneys to do when investigating other aspects of a criminal case, including even immigration law provisions central to guilt or punishment. This Article locates Padilla within a quarter-century of Strickland analyses and contends that the new Strickland-lite approach conflicts with Strickland’s mandate and fails to remedy the problem of inaccurate advice for noncitizen criminal defendants that Padilla purports to remedy.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".