Bibliographic record
Abstract
Artiklen behandler temaet god fondsledelse i såvel erhvervsdrivende som ikke-erhvervsdrivende fonde. Emnet er relevant eftersom fonde har en markant anderledes struktur end andre selskabsformer, hvilket især gør sig gældende med hensyn til ejerstrukturen. For det første er fonde selvejende, hvilket indebærer at fondene ikke har nogen ejere, der på en generalforsamling kan afsætte og indvælge bestyrelsesmedlemmer. Udpegning af bestyrelsesmedlemmer må derfor finde sted på anden vis, for eksempel - og meget hyppigt - ved selvsupplering. For det andet er en fond stiftet ved en vederlagsfri disposition, hvorved stifteren ensidigt har fastsat fondsvedtægtens indhold, herunder hvem der skal udgøre bestyrelsen og eventuelt tillige hvorledes bestyrelsen fremtidigt skal sammensættes. For det tredje indebærer fraværet af ejere, at fondene er undergivet offentligt tilsyn i form af Civilstyrelsen hhv. Erhvervsstyrelsen samt kritisk revision af fondens revisor. Artiklen inddrager Erhvervsfondsudvalgets rapport og forslag til nye lovbestemmelser samt udkast til anbefalinger om god fondsledelse.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.375 | 0.251 |
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".