30 años de investigación en maltrato infantil: un análisis bibliométrico (1991-2020)
Bibliographic record
Abstract
Introduction: Child abuse is a global problem that affects children’s development and can have consequences throughout their lives. Despite the need to research to eradicate this phenomenon, there has not been a bibliometric approach to its recent advances. Method: This study examined 16,708 articles on child abuse indexed in the Web of Science between 1991 and 2020 to establish research trends. Results: Child maltreatment is an active field, mainly influenced by the USA, Canada and the UK, and journals in the family studies category, especially Child Abuse & Neglect. The most relevant articles address the topic as part of Adverse Childhood Experiences or focus on its assessment. Considering the most relevant articles, the most studied topics (subjects, research, maltreatment and types of maltreatment, family and parenting, and disorders) and the main foci (maltreatment, research, sex, reporting, and sexual abuse), it is possible that the area is being restructured under the ecobiodevelopmental perspective, with emphasis on treatment and prevention. Its theoretical and practical implications are discussed. Conclusions: This study updates research trends in the field of child maltreatment, providing a comprehensive overview that suggests an evolution toward the integration of multiple disciplines and approaches. The results highlight the importance of further research on this global problem, as well as the need to evaluate existing interventions to reduce its impact on children’s development.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.017 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.033 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".