Bibliographic record
Abstract
In 2019, the now 187-member International Labour Organization celebrated its 100 th anniversary.As one of the oldest agencies of the United Nations, the ILO used the occasion to renew calls for improved opportunities and working conditions, social protections and collective bargaining rights.The ILO's Global Commission on the Future of Work (2019, 2) proposed a "human-centred agenda for the future of work that strengthens the social contract by placing people and the work they do at the centre of economic and social policy and business practice."Because the world of work begins at home, this included calls for new investments that more evenly distribute unpaid care work, from parental leave to public care services, thereby genuinely increasing opportunities in the workplace; universal entitlements to lifelong learning via active labour market policies that provide opportunities for re/upskilling; proactive universal social protections that support people's needs over the life cycle; new investments in the institutions of work, from regulations and employment contracts to collective bargaining and labour inspection systems; expanded "time sovereignty," that is, the right to disconnect from work and greater autonomy over working time; and harnessing technology -artificial intelligence, automation and robotics -in a manner that prioritizes human well-being, regulates data use and algorithmic accountability in the world of work.The Commission (2019, 3) also called for establishing a Universal Labour Guarantee: "All workers, regardless of their contractual arrangement or employment status, should enjoy fundamental workers' rights, an "adequate living wage" (ILO Constitution, 1919), maximum limits on working hours and protection of safety and health at work."They stress urgent action is needed to develop national strategies on the future of work and transformative investments that meet the challenges of climate change.There is a vast gap between this call for living wages and fundamental rights, and the reality most workers face in the workplace.For decades, employers have been attempting to increase profit margins by re-organizing work.This includes subcontracting, offshoring, converting full-time jobs to part-time and temporary, and reclassifying direct employees as independent contractors.This is
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.017 | 0.027 |
| Insufficient payload (model declined to judge) | 0.061 | 0.028 |
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".