Think Tank Deliberates Future Directions for the Social Approach to Aphasia
Bibliographic record
Abstract
Abstract Purpose : This article describes the rationale and outcome of an international meeting held to explore evidence related to social approaches to aphasia intervention. Method : A think tank and conference took place in Toronto, Canada, in September 2007 with the purpose of mobilizing a process of collaboration to document and collect evidence related to social approaches to aphasia. Using a framework called “Living with Aphasia: Framework for Outcome Measurement” (A-FROM), meeting participants worked to identify evidence available in the literature related to social approaches, identify gaps in evidence, and establish a plan to move forward in the process of establishing a comprehensive evidence base. Results : A preliminary summary of evidence was defined according to A-FROM domains, and weaknesses and gaps were identified. Concrete directions for the future were set forth as action plans. Conclusions: This report on the outcomes of the international think tank serves as an invitation to those interested in furthering the evidence for social approaches to aphasia to become involved in a collaborative process of evaluating and collecting evidence.
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 | 0.203 | 0.154 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.024 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.014 | 0.024 |
| Insufficient payload (model declined to judge) | 0.017 | 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".