Understanding consumer influences on product lifetimes: the \nIndividual-Practice Framework
Bibliographic record
Abstract
In the field of sustainability, understanding consumer influences on product lifetimes is deemed essential to reduce the environmental impact of consumption. The aim of the research project which informs this paper was to investigate different ways of thinking about how consumers’ values may contribute to the acceptance, adoption and diffusion of collaborative consumption – an economic model based on sharing, lending, swapping, gifting, bartering, or renting products and services enabled by network technologies and peer communities (cf. Botsman and Rogers, 2011). By making it possible to obtain use of goods without owning them, these alternative patterns of consumption have some potential to prevent new purchases, intensify product usage and promote reuse of possessions that are no longer wanted, thus contributing to longer product lifetimes. \n \nThe relationship between values and the participation in collaborative consumption was explored through mixed methods research drawing from two different, if not contrasting, theoretical perspectives to understand consumer behaviour: social psychology and social practice theory. Drawing on their possible complementarity, the investigation was structured in two subsequent and interactive phases: a quantitative data collection and analysis, followed by a qualitative strand of research. The initial quantitative study measured individual values through use of Schwartz's PVQ-R3 tool. Results were followed up through semi-structured interviews facilitated by a series of visual prompts. This paper presents the resulting Individual-Practice Framework, which uniquely combines insights from social psychology and social practice theory to examine and explain the interrelation between the individual, his/her personal values, and specific combinations of the ‘material’, ‘meaning’ and ‘competence’ elements that sustain social practices.
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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 | 0.015 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.053 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".