Displaying Families, Migrant Families and Community Connectedness: The Application of an Emerging Concept in Family Life
Bibliographic record
Abstract
The new concept of Displaying Family shows how family life must not only be 'done' but also be 'seen to be done'. Both family members and external audiences need to recognise what is being conveyed during such displays—and to accept them—for these displays to be considered successful. Hence, there are multiple potential audiences for family displays. Drawing on empirical research, the article applies this important conceptual development to a study of the role of family in promoting community connectedness in a UK city which is becoming increasingly culturally diverse. Specifically, it examines the use of family display by migrant families and the observation of this by multiple audiences. The paper will consider early findings on the impact family display has on the forging of interactions and connectedness between communities and the development of a 'world building' rather than a 'nation building' sensibility. By acknowledging that the ideology of the family has both overarching themes but contextually varied interpretations, it will examine the potential of family displays—and their receipt—to allow the recognition of similarities between culturally diverse groups and to bridge the differences that extend beyond family. The article will present data from individual and group interviews with migrant families, including children, and other potential audiences of family displays to illustrate the application of this new concept.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".