Association for Conflict Resolution Guidelines for Eldercaring Coordinators
Bibliographic record
Abstract
On November 6, 2014, the AFCC Board of Directors endorsed the Association for Conflict Resolution (ACR) Guidelines for Eldercaring Coordination, including ethical principles for Eldercaring Coordinators, training protocols, and court pilot project template. The collaboration between Task Forces created by ACR and the Florida Chapter of AFCC, composed of twenty U.S./Canadian and twenty Florida‐wide organizations, produced both an overarching guide to assist in the development of programs and a more detailed model addressing state/province‐specific needs and characteristics. Eldercaring coordination is a dispute resolution option specifically for high‐conflict cases involving the care, needs, and safety of elders. Key Points for the Family Court Community: There are currently no dispute resolution options for parties involved in high‐conflict cases regarding the care, needs, and safety of an elder. The ACR Guidelines for Eldercaring Coordination address the discrepancies between dispute resolution options available for parents in conflict regarding their minor children and mature families with unresolved concerns about the care, needs, and safety of an elder. The ACR Guidelines for Eldercaring Coordination provide information regarding the ethical practice of eldercaring coordination including a specific definition, recommended qualifications, ethical practices, grievance procedures, training protocols, and a court pilot project template. The practice of eldercaring coordination will address the influx of court cases expected as baby boomers continue to age, reducing delays in court hearings, as parties will have the opportunity to resolve their concerns without continuous court attention. As of June 2015, five states began Pilot Projects on Eldercaring Coordination, which will be studied by an independent research group to enhance the progress of the process and to develop the best practices for initiating the programs elsewhere.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".