Play, Learn, and Teach Outdoors—Network (PLaTO-Net): terminology, taxonomy, and ontology
Bibliographic record
Abstract
BACKGROUND: A recent dialogue in the field of play, learn, and teach outdoors (referred to as "PLaTO" hereafter) demonstrated the need for developing harmonized and consensus-based terminology, taxonomy, and ontology for PLaTO. This is important as the field evolves and diversifies in its approaches, contents, and contexts over time and in different countries, cultures, and settings. Within this paper, we report the systematic and iterative processes undertaken to achieve this objective, which has built on the creation of the global PLaTO-Network (PLaTO-Net). METHODS: This project comprised of four major methodological phases. First, a systematic scoping review was conducted to identify common terms and definitions used pertaining to PLaTO. Second, based on the results of the scoping review, a draft set of key terms, taxonomy, and ontology were developed, and shared with PLaTO members, who provided feedback via four rounds of consultation. Third, PLaTO terminology, taxonomy, and ontology were then finalized based on the feedback received from 50 international PLaTO member participants who responded to ≥ 3 rounds of the consultation survey and dialogue. Finally, efforts to share and disseminate project outcomes were made through different online platforms. RESULTS: This paper presents the final definitions and taxonomy of 31 PLaTO terms along with the PLaTO-Net ontology model. The model incorporates other relevant concepts in recognition that all the aspects of the model are interrelated and interconnected. The final terminology, taxonomy, and ontology are intended to be applicable to, and relevant for, all people encompassing various identities (e.g., age, gender, culture, ethnicity, ability). CONCLUSIONS: This project contributes to advancing PLaTO-based research and facilitating intersectoral and interdisciplinary collaboration, with the long-term goal of fostering and strengthening PLaTO's synergistic linkages with healthy living, environmental stewardship, climate action, and planetary health agendas. Notably, PLaTO terminology, taxonomy and ontology will continue to evolve, and PLaTO-Net is committed to advancing and periodically updating harmonized knowledge and understanding in the vast and interrelated areas of PLaTO.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".