Bibliographic record
Abstract
De reclasseringswerker komt in de dagelijkse praktijk soms voor morele dilemma‟s te staan. \nEen moreel dilemma ontstaat wanneer essentiële waarden met elkaar in strijd zijn en de keus voor de ene waarde het realiseren van de andere waarde onmogelijk maakt. \nOplossen, in de zin van „de kool en de geit sparen‟ is niet mogelijk, anders was het geen dilemma. \nErin blijven hangen omdat je de keus voor het ene niet kan verkiezen boven de keus voor het andere is evenmin mogelijk. Je moet handelen en tot een keus komen. Welke keus? En hoe kom ik tot een besluit? Deze vraag kan je systematisch bespreken, met collega‟s of werkbegeleider. Hoe doe je dat? En waarom is dat belangrijk?
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 | 0.022 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.025 |
| Scholarly communication | 0.014 | 0.023 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.016 | 0.016 |
| Insufficient payload (model declined to judge) | 0.051 | 0.008 |
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".