Bibliographic record
Abstract
On May 1, 1997, Tony Blair and his New Labour Party won the British general election with 43.2 percent of the vote, against 30.7 percent for the Conservatives and 16.8 percent for the Liberal Democrats. Coming from a distance, the Labour Party won more seats than ever in its history. It progressed in every region and in most social groups, among the less fortunate and the young in particular. After eighteen years in opposition, the British left was finally able to form a strong and legitimate majority government. This was, however, a new left. A New Labour government, Blair had promised, would define a new course, away “from the solutions of the old left and those of the Conservative right,” and focused on “what works.” Tony Blair was not alone. A few years earlier, in 1992, Democrat Bill Clinton was elected president of the United States with a commitment to “reinvent government” and restore the responsibility of citizens and a sense of community. “The change I seek and the change that we must all seek,” Clinton had explained in October 1991, “isn't liberal or conservative. It's different and it's both.” In October 1993, Canadians replaced the Conservatives, in power since 1984, with the centrist Liberal Party, led by Jean Chrétien. In continental Europe, social-democrats were also coming to power, in one country after the other.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.020 | 0.008 |
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".