The ILO’s Role in Global Governance: Limits and Potential
Bibliographic record
Abstract
The International Labour Organization (ILO) has demonstrated a remarkable ability to adapt to changing conditions throughout its long history. At its centenary, the ILO must once again respond to evolving circumstances and find new ways to engage state and private actors participating in an interconnected global economy where labour standards continue to be violated and where work itself is undergoing significant transformations. This chapter explores recent efforts by the ILO’s leadership to reassert the organisation’s role in broader global policy contexts. Part one presents the concept of institutional layering in order to understand better the agents of change and the structures in which they operate. The three sections that follow demonstrate institutional layering across three core dimensions of global governance—actors, rules, and mechanisms—in the period since 1998. The chapter concludes that the ILO’s current governance practices have mixed prospects for the organisation’s role in a changing governance landscape. New layers of soft law rules and flexible governance mechanisms can potentially augment the ILO’s global standing moving forward. Its lack of representativeness and its continuing engagement of new actors, however, demand further formal changes to the ILO’s institutional apparatus.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.042 |
| Scholarly communication | 0.026 | 0.020 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".