Bibliographic record
Abstract
Throughout his long and distinguished career, Ernest House has continuously stressed the moral responsibility of evaluators. His social activist perspective has time and again alerted us to the dangers of being seduced by the agendas of those in power. (It was this stance that made him a particularly appropriate keynote speaker for Saskatchewan’s first CES annual conference; he is well versed in Saskatchewan’s history of co-operatives and social initiatives.) In his keynote address, he points out that the current political climate in the United States presents a threat to the independence and utility of evaluation, that is, the threat of becoming a servant of the power elite. Using Janice Gross Stein’s analysis of the cult of efficiency, he shows how political fundamentalism and methodological fundamentalism are intimately linked. As he wrote over 25 years ago in his monograph The Logic of Evaluative Argument (1977): “There are those who try to force simplicity atop the complexities of life and thereby eradicate ambiguity ... Often in positions of power, they impose arbitrary definitions of reality for the sake of action” (p. 47).
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 | 0.058 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.018 | 0.091 |
| Scholarly communication | 0.041 | 0.023 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".