Bibliographic record
Abstract
Abstract The use of public procurement to achieve social outcomes is widespread, but detailed information about how it operates is often sketchy and difficult to find. This article is essentially a mapping exercise, describing the history and current use of government contracting as a tool of social regulation, what the author calls the issue of ‘linkage’. The article considers the popularity of linkage in the 19 th century in Europe and North America, particularly in dealing with issues of labour standards and unemployment. The use of linkage expanded during the 20 th century, initially to include the provision of employment opportunities to disabled workers. During and after World War II, the use of linkage became particularly important in the United States in addressing racial equality, in the requirements for non‐discrimination in contracts, and in affirmative action and set‐asides for minority businesses. Subsequently, the role of procurement spread both in its geographical coverage and in the subject areas of social policy that it was used to promote. The article considers examples of the use of procurement to promote equality on the basis of ethnicity and gender drawn from Malaysia, South Africa, Canada, and the European Community. More recently, procurement has been used as an instrument to promote human rights transnationally, also by international organizations such as the International Labour Organisation. The article includes some reflections on the relationship between ‘green’ procurement, ‘social’ procurement, and sustainable development, and recent attempts to develop the concept of ‘sustainable procurement.’
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".