Kelalaian Pencatatan Nikah Pada Perkawinan di Bawah Umur di Kabupaten Gorontalo
Bibliographic record
Abstract
Marriage registration is important in marriages in Indonesia because it can have legal consequences for those who carry out marriages. This study discusses the form of negligence of marriage registration in underage marriages in Gorontalo District and the legal consequences that occur due to negligence of marriage registration in age marriages in Gorontalo Regency. This research is a field research with a juridical and sociological approach. The collection of data in the form of observations at the study site, interviews with employees of the Office of Religious Affairs, parents and underage marriages with 182 respondents, as well as literature review. The results showed: First, the form of negligence in the registration of marriages in Gorontalo Regency, namely the negligence of parents, the negligence of children and the negligence of marriage registration officers; Second, due to the legal consequences caused by negligence in registering underage marriages in Gorontalo District, namely the legality of child marriages, divorce is easy, rejection of marriage dispensation, repeating the marriage contract and marriage without the presence of government officials.
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 | 0.000 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".