Bibliographic record
Abstract
As noted in Chapter Four, the main difference in the evolutionary path for social alarms or personal response systems and services (PRS) in North America arises from the fact that their development was almost entirely a private sector phenomenon, with such services being promoted on the basis of cost savings in healthcare. This contrasts markedly with the position in Great Britain where, as was noted in Chapters Five and Six, development predominantly took place within the public sector and was concerned with housing and social welfare agendas. This is not to suggest that there was no overlap or common ground between the respective experiences. Both, as with other developed countries, experimented with bell and buzzer systems in the context of different types of accommodation, such simple technologies becoming particularly commonplace in institutions. However, the ensuing paths were divergent. In Canada, common ground has been evident mostly with the United States and relates to the fact that social alarms (PRS) were seen as relevant, at least in part, to private sector healthcare services. There is also, however, some common ground with Great Britain relating to the recognition that social alarms are also relevant to the needs of older people in public sector housing. The Canadian context is one where there are relatively high levels of public sector housing provision in some areas. In 1992, for instance, there were 46,000 public sector dwellings for older people in the province of Ontario (Hobbs, 1992, p 24). PRS installations had at this time already been made in the context of healthcare facilities and nursing homes, reflecting the nature of developments in the United States.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".