The evolving family assemblage: how senior families “do” family
Bibliographic record
Abstract
Purpose A growing stream of consumer research has examined the intersection of family dynamics, consumption practices and the marketplace. The purpose of this paper is to make sense of the complex nature of family for senior families (adult children and their elderly parents) who employ the use of elder care services and facilities. Design/methodology/approach This research analyses data gathered from in-depth interviews with adult siblings and their elderly parents through the lens of assemblage theory. Findings This paper advances a conceptulisation of the family as an evolving assemblage of components, including individual members; material possessions and home(s); shared values, goals, memories and practices; prominent familial attributes of love and care; and marketplace resources. Three features of the assemblage come to the fore in senior families: the fluid meaning of independence for the elderly parent, the evolution of shared family practices and the trajectory of the assemblage that is a function of its history and future. Originality/value This research focuses on a stage of family life that has been under-theorised; applies assemblage theory to the family collective, demonstrating that a family can be conceptualised as an ever-evolving assemblage of human and non-human components, and this is a useful lens for understanding how senior families “do” family; and argues for a broader notion of family – one that is not household-centric or focused on families with young children, that encompasses members and materiality and that foregrounds the dynamic, evolving nature of family life.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".