Caregiving for the Elderly Person: Discourses Embedded in the Brazilian <i>Practical Guide for the Caregiver</i>
Bibliographic record
Abstract
It is estimated that in 2025, Brazil will have the sixth largest elderly population in the world. Beyond the economic consequences of this projection, this changing demographic portends significant changes in the social realm. The aim of this study was to review and consider a range of government documents, developed during the past thirty years and directed toward elderly Brazilian citizens, to explore the ways that caregivers of older persons are positioned in daily care practices through the discourses such documents deploy. The analysis draws on Foucault's genealogical approach, and begins with a review of the historicity of policies, regulations, and legislation related to older people, followed by an analysis of the discourses embedded in the Practical Guide for the Caregiver, a document created by the Brazilian Ministry of Health to provide guidance to informal caregivers in the actual provision of care to elders. The analysis shows that throughout the Guide, caregivers are portrayed as multifaceted subjects; yet at the same time, three primary positionings for the caregiver and her or his work are emphasized: the almost-angel, the almost-healthcare professional, and the almost-household professional.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.024 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".