Case-aides in welfare agencies : a review of the values, possibilities, and methods of utilizing case-aides, paid and volunteer, in various welfare settings
Bibliographic record
Abstract
There are several important reasons for considering the use of case-aides in welfare programs. One is the shortage of professional personnel and the need for trained workers. Further, citizen participation is essential in order to gain the understanding and feel the responsibility to support the agencies which are dependent upon the lay public for their life-blood. Moreover, modern social work emphasizes the value of personal relationships in the helping process. Experience in the use of case-aides, paid or volunteer, is studied from a review of existing manuals and agency programs which are either currently or recently in practice In the welfare field in the United States and Canada. A canvass of the directors of selected casework agencies in Vancouver provides viewpoints and information for comparative use in the study. Current practices are summarized to suggest standards and opportunities for further development of this trend in social work. Both problems and values are outlined. It is the conclusion of the study that a well-formulated case-aide program can utilize the helpfulness of the volunteer without risk to the profession of social work. The success of the endeavor, however, is dependent upon careful selection, training and supervision of the case-aide, with detailed care in planning. Case-aides can not only supplement the work of the professional caseworker, but can extend the services of the agency, performing many tasks needed by the client but not appropriate for the professional. The crux of the situation is "job analysis” which will lead to systematic sharing of responsibilities with case-aides, paid or volunteer. In Vancouver, paid case-aides are being used to a limited extent. Volunteer case-aides are not being used as a part of a formulated program by agencies, singly or co-operatively. The need of the services is recognized by several directors and staff members but no programs have yet been inaugurated. Areas which might utilize such services include the aged, the handicapped, needy children, immigrants, chronically ill, mental patients, and clients and families of medical social service departments.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".