Social protection guarantees as legal rights? The International Labour Organization, the United States, and the American ‘national context’
Bibliographic record
Abstract
This article examines the development of the global Social Protection Floor proposal inside the International Labour Organization (ILO) from 2009 (when the ILO was designated as a lead agency in the process) through to the adoption of Recommendation 202 in 2012. While there was a considerably more high-profile external process under the auspices of the Advisory Group chaired by former Chilean President Michelle Bachelet, the article argues that it was in the internal ILO process that debates regarding the most important substantive elements of the Recommendation were resolved. The United States was vigorously involved in this process and had a crucial influence on the substantive development of Recommendation 202. First, US involvement played a key role in limiting the degree to which – and manner in which – the recommendation would apply to medium- and high-income countries with established social protection systems. Second, the United States contributed to successfully blocking the definition of social protection as comprising sets of legally enforceable entitlements enshrined in national legislation. This marked a significant shift in the substantive meaning of the recognition of a human right to social protection. US efforts in this regard can be understood as the result of its concern regarding the uneasy fit between a potential recommendation and its own domestic social protection provision.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.027 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".