Development of a digital photo hoarding scale: A research with undergraduate students
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study focuses on hoarding of digital assets. Today people's ownership of digital assets can be uncontrolled and the measurement tool designed in the study is expected to be useful for young people, health care organizations, businesses (smartphone firms etc.) and researchers. In the study, previous researches on hoarding, in particular hoarding of digital assets are reviewed. We then describe the process by which we developed our digital photograph hoarding scale (DPHS): development of scale items, evaluation of items, testing of a preliminary version, conducting validity and reliability analyses and analysis of scale scores. As a result, sub-dimensions of the digital photograph hoarding are identified as: problems caused by uncontrolled acquisition of photographs; problems caused by clutter; uncontrolled clutter of photographs; failure to dispose of photographs and related problems; uncontrolled taking of photographs accompanied by a constant desire to do so. It is seen that people with high DPHS scores also have higher scores on measures of photographing and photograph examination. Finally, the limitations of the research are discussed and suggestions for the future researches are offered.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it