Employment policy confronted with new patterns of governance centred on coordination and performance
Bibliographic record
Abstract
At both the global and local levels, employment policy currently constitutes one of the major issues confronted by governments faced with economic crises and globalization. The success of these policies depends, in particular, on their ability to link together initiatives undertaken not only at different levels of power, but also within a single level between multiple actors that (more or less) have prerogatives in matters of employment policy. This domain of public policy constitutes a unique space in which to analyse the developments and circulation of principles promoted by advocates of two new patterns of governance: New Public Management and the Open Method of Coordination. On the basis of a qualitative analysis conducted with employment policy actors in the Brussels-Capital Region (BCR), this article studies the difficulties these actors come up against when faced with the implementation expectations of new managerial demands, as well as coordination demands that force an increasingly flexible economic landscape and an increasingly complex institutional landscape onto these actors. Enumerating the difficulties encountered, the article also updates the strategies put into place by the actors themselves to address the often severe diagnoses that are made of the situations to which they are subject. This article also constitutes a contribution to the clarification of both the favourable and undesirable conditions for the establishment of new forms of governance within public policy. Points for practitioners In most countries, employment policies figure among the highest priorities. When new initiatives in this sector need to be elaborated and implemented, practitioners attempt to balance a wide variety of opinions, focusing on the coherence of their decisions and actions. In the context of performance management, practitioners are also required to demonstrate the success of their public interventions. In Europe, these expectations are exacerbated by the requirements of the Open Method of Coordination and New Public Management. The appropriation of these two patterns of governance depends on a given practitioner’s receptivity regarding the perceived utility of these patterns to their particular work.
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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 | 0.024 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.059 |
| Scholarly communication | 0.023 | 0.013 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".