Bibliographic record
Abstract
In discussions with older adults on their engagements with cell/smart phones, mobile devices and computers (n 300+) the question of time is often part of the conversation implicitly or explicitly. The need for time management to minimize cost; the sense of a gap in generations who use different media; the desire to “hang on” to devices until they no longer function. These are but a few examples that illustrate how the connections between media and time, or perhaps more specifically the experience of temporality, emerged in conversations with Canadian mobile phone users 65 and over. Drawing on this interview data, this paper explores these connections. Further, I propose that the processes of ageing are one way for age studies researchers to gain insight into the experiences of media and temporality (Taylor, Jodie, 2010). In this respect, this paper is not ‘about’ ageing. Rather, ageing as a complex intersectional process of bio-social change, is explored as a “method of inquiry” to better understand time, temporality and changes in media practices.
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 | 0.036 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".