The Harder They Fall? A Response to Wickens et al. (2019) Regarding the Generalizability of Lumberjack Predictions to Complex Work Settings
Bibliographic record
Abstract
OBJECTIVE: This article is a response to Wickens et al.'s (2019) critique of Jamieson and Skraaning (2019). BACKGROUND: Wickens et al. (2019) offer a five-point critique of Jamieson and Skraaning (2019) that they claim tempers the strength of our conclusions. APPROACH: We first correct a misrepresentation in the critique and then respond to each of the criticisms. RESULTS: We preserve the strength of our skeptical conclusions about the applicability of the lumberjack model to complex work settings. APPLICATIONS: We continue to caution system designers about the lack of evidence supporting the lumberjack model in the context of complex work systems.
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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 | 0.064 | 0.233 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.023 | 0.040 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".