Bibliographic record
Abstract
Purpose: To develop a transdisciplinary conceptualization of social belonging that could be used to guide measurement approaches aimed at evaluating the effectiveness of community-based programs for people with disabilities.Method: We conducted a narrative, scoping review of peer reviewed English language literature published between 1990 and July 2011 using multiple databases, with “sense of belonging” as a key search term. The search engine ranked articles for relevance to the search strategy. Articles were searched in order until theoretical saturation was reached. We augmented this search strategy by reviewing reference lists of relevant papers.Results: Theoretical saturation was reached after 40 articles; 22 of which were qualitative accounts. We identified five intersecting themes: subjectivity; groundedness to an external referent; reciprocity; dynamism and self-determination.Conclusion: We define a sense of belonging as a subjective feeling of value and respect derived from a reciprocal relationship to an external referent that is built on a foundation of shared experiences, beliefs or personal characteristics. These feelings of external connectedness are grounded to the context or referent group, to whom one chooses, wants and feels permission to belong. This dynamic phenomenon may be either hindered or promoted by complex interactions between environmental and personal factors.Implications for RehabilitationSense of belongingProgram evaluation and monitoring exist in order to measure success and outcomes of rehabilitation practice.Sense of belonging is one of the goals of rehabilitation services, but has not yet been defined unambiguously, making it difficult for practitioners to understand if they are achieving these goals.Researchers and practitioners in rehabilitation can define a sense of belonging as a subjective feeling of value and respect derived from a reciprocal relationship to an external referent that is built on a foundation of shared experiences, beliefs or personal characteristics when conceptualizing and designing tools to measure sense of belonging as an outcomes of their services.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.007 | 0.036 |
| Scholarly communication | 0.009 | 0.018 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".