The Anti-Mattering Scale: Development, Psychometric Properties and Associations With Well-Being and Distress Measures in Adolescents and Emerging Adults
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
Previous work has focused on positive feelings of mattering, which pertain to the human need to feel significant. In the current article, we examine a complementary yet distinct construct involving feelings of not mattering that may arise from being marginalized and experiences that heighten a sense of being insignificant to others. We also describe the development, validation, and research applications of the Anti-Mattering Scale. The Anti-Mattering Scale (AMS) is a five-item inventory assessing feelings of not mattering to other people. Psychometric analyses of data from samples of emerging adults and adolescents confirmed that the AMS comprises one factor with high internal consistency and adequate validity. Our findings suggest that individuals who feel like they do not matter to others have a highly negative self-view, insecure attachment, and perceived deficits in meeting key psychological needs. Analyses established that links between elevated AMS scores and levels of depression, social anxiety, and loneliness. Most notably, scores on this new measure predicted unique variance in key outcomes beyond the variance attributable to other predictors. Overall, these results attest to the research utility and clinical potential of the AMS as an instrument examining the tendency of certain people to experience a profound sense of not mattering to others in ways that represent a unique source of risk, social disconnection, and personal vulnerability.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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