Bibliographic record
Abstract
There have been different opinions on the characteristics of harmful behavior among which the common view thinks that harmful behavior has three characteristics: Corporeality; Intentionality; Harmfulness. When judging these views, we need to treat harmful behavior as basic, core, boundary, combination element in the system of constitutive elements of crime. As the basic element, harmful behavior should explain various kinds of crimes. The reasoning and argument should be comprehensive. However, intentionality has excluded actio libera in causa and vergelichkeitsdelikt outside of harmful behavior so it cannot be recognized as characteristic of harmful behavior. As the core element, harmful behavior must reflect the nature and legal characteristics of crime which indicates that harmfulness and illegality must be the characteristics of harmful behavior. As the boundary element, harmful behavior exclude pure mental activities via corporeality out of crime, therefore, corporeality should of course be the characteristic of harmful behavior. Key words: Harmful Behavior; Corporeality; Intentionality; Harmfulness; Illegality
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.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.004 | 0.062 |
| Scholarly communication | 0.009 | 0.025 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".