<i>Networking Enforced</i>–<i>Comparing Social Services</i>'<i>Collaborative Rationales across Different Welfare Regimes</i>
Bibliographic record
Abstract
Abstract Collaboration and networking are ubiquitous,versatile features of social service provision in most Western countries. However,it is an open question whether networking means and entails the same across countries. Comparing regulatory frameworks in three jurisdictions representing distinctive‘worlds of welfare services’ –Germany,Norway and Quebec–this article aims at eliciting the normative rationales that underpin and inform local service networks in child welfare and protection(CWP)systems. In Norway,where services are little diversified and largely insular,networking appears as a way of opening up for greater organizational plurality,within and beyond the public sector realm. In Germany in contrast,where services are highly pluralized and fragmented,networks are seen as an instrument for streamlining complexity. As for Quebec–an intermediate case in some respects–networking is envisioned as a catalyst for aligning two co‐existing service streams and mitigating the child protection–family support divide. Interestingly,in all three places,networking is now being enforced through similar highly formalized,top‐down regulatory provisions,even though the intended directions of change differ markedly. This has implications for CWP policy as well as research on networks at large.
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 | 0.026 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.025 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".