Bibliographic record
Abstract
Foreword Acknowledgements I. Introduction Thinking Differently Empowered Customer II. Developing Customer Orientation The Continuing Demand for Quality Citizens as Customers Recent Initiatives III. Empowering the Socially Deprived The Socially Deprived and Vulnerable Meeting the Needs of Socially Deprived Groups Giving Voice to the Vulnerable IV. Charters and Service Standards What is a Service Charter? Charter Themes and Development Impact and Achievements V. Developing and Implementing Service Charters Introduction Key Implementation Steps Problems to Watch VI. The Service Charter in Practice Background The Charter in Operation since 1991 What has the Charter Achieved? Future Plans for the Charter VII. Consumer Protection Institutions and Strategies Introduction Legislation Consumer Organisations Consumer Education and Representation VIII. Consumer Organisations at Work The 'Space' for Consumer Organisations The History of the Consumers' Organisation of Canada since 1897 Four Institutions Crucial to Market Success What Does the Canadian Experience Mean for Other Countries IX. Product Testing and Quality Assurance Introduction Comparative Product Testing Safety Standards and Ensuring Quality Bibliography Appendix 1. Excerpts from the Charter for the Public Services in Africa Appendix 2. Sample Service Charter (NHS, United Kingdom)
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".