Bibliographic record
Abstract
This article examines how the International Labour Organization’s (ILO) Decent Work agenda integration into poverty reduction strategies has provided the wherewithal for closer cooperation with the International Monetary Fund and the World Bank. It begins by discussing multilateral approaches to poverty reduction and identifying criticisms of structural adjustment programmes and the policy prescriptions of the Washington Consensus as key prompts for closer cooperation with the ILO. The article examines the development of the ILO and identifies the role that successive Director Generals have played in repositioning it as a key player in multilateral approaches to poverty reduction. The complex nature of cooperation between the ILO and the International Financial Institutions (IFIs) is acknowledged and discussed. While the Washington Consensus has not been abandoned, analytical shifts within the IFIs, including greater acknowledgment of the role labour market institutions can make in sustainable growth and development, have prompted closer integration between employment and social policies and international macroeconomic policy strategies. At the heart of this engagement lies the ILO’s Decent Work Agenda and the demand for greater policy coherence among multilateral organizations in poverty reduction. The integration of Decent Work into IFI Poverty Reduction Strategy Papers (PRSPs) is identified as a key platform for these activities. The article describes the ILO strategy for integrating Decent Work into the PRSP process and examines the criticisms this strategy has attracted. In highlighting the importance of worker voice in the national delivery of poverty reduction strategies, the article concludes by promoting the need for representative bodies to have the necessary organization and skills to engage with and implement poverty reduction strategies. For Decent Work and poverty reduction to succeed, this need is of both a national and international concern. Such challenges loom large in future engagement between the ILO and the IFIs.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.040 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".