Bibliographic record
Abstract
In the child and youth care sector, protecting vulnerable children is a key priority, one that requires a skilled workforce capable of meeting diverse and complex needs. Starting with an acknowledgement of the field’s struggle for identity, this article briefly recounts highlights of our journey to achieving recognition as a profession, with an emphasis on the South African context. The profession’s early phase is described along with the key developments that have shaped the scope of practice, leading to a discussion of current matters that have the potential to transform the field, and ideas regarding priorities that may need to be considered for a longer-term agenda. Reflections on a journey that builds on lessons from South Africa as they connect to a wider global context are shared. The initiatives shared within this journey reflect a resilient sector that has contributed to the creation of employment opportunities for child carers. They also provide some milestones for the formalising of a sector that requires regulation because of the vulnerable population it serves. From the emerging priorities, pointers for the next steps in the profession’s journey are offered.
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 | 0.030 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.032 | 0.064 |
| Scholarly communication | 0.027 | 0.035 |
| Open science | 0.003 | 0.041 |
| Research integrity | 0.012 | 0.024 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".