How Do We Perceive The Phenomenon of "Co-Parenting"? Do We Share Responsibilities Sufficiently?: A Bibliometric Study
Bibliographic record
Abstract
The primary objective of this study is to assess co-parenting research through bibliometric analysis. The documents under evaluationwere sourced from the Web of Science (WoS) database. Initially, 473 studies were were retrieved using keyword "co-parenting". Subsequently, after applying exclusion criteria, a comprehensive bibliometric and content analysis was conducted on the remaining 421 articles. These studies were classified and visually represented based on their characteristics. It was determined that the studies evaluated within the scope of the study were conducted between 1981 and 2023. The analysis revealed that the author with the highest number of publications was O. Cohen and the most productive institution was "University of Toronto". Co-parenting, divorce, parenting, and fathers emerged as the most frequently recurring keywords through co-keyword analysis. Furthermore, the study titled "The internal structure and ecological context of co-parenting: A framework for research and intervention" was identified as the most cited study through co-reference analysis. The study concludes that Paul R. Amato was the most influential author in the co-citation analysis, while Marsha Kline Pruett was the most influential author in the co-author analysis.
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
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 | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.033 | 0.150 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.116 | 0.182 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".