RELATIONSHIP OF LUNAR PHASES TO CRIMES COMMITTED IN ZAMBOANGA DEL NORTE
Bibliographic record
Abstract
Human behavior appeared to be influenced by lunar phase. Crimes still committed despite the government efforts to prevent and suppress it. Some authors claimed that the moon of the solar system affect the human body and the planet earth. The term lunacy derived from the idea that the lunar cycles affect human behavior and it is a widely believed phenomenon that a full moon can increase criminal behavior. This study aimed to determine the relationship between lunar phases and crimes committed in the two cities of Dipolog and Dapitan. Documentary analysis and unstructured interviews were conducted to gather information. The data were taken from the reported crimes in the two police stations. Statistical tools used were frequency count and chi-square test of both difference and relationships respectively. The most common index crimes were theft, physical injury and threat. Whereas, non-index crimes were malicious mischief and violations to RA 7610 and RA 9262. Results revealed that most of the index crimes happened during the first quarter and during new moon phase. Non-index crimes on the other hand, happened at any lunar phase. The occurrence of index and non-index crimes are likely to be influenced by the lunar phases. Philippine National Police might set-up additional preventive measures to prevent would be criminals from committing theft, physical injury and threat. Police presence be increased more during first quarter and new moon phases to prevent occurrence of crime as well as implement intensive community policing program to protect the community from untoward crime incidence.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".