Advances in relational competence theory : with special attention to alexithymia
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
Preface In Support of Theory in Applied Research & Practice A Hierarchical Framework for Relational Competence Theory Updating the Alexitymia Construct & its Measurement Understanding Alexithymia through an Information Processing Model Relational Competence & Alexithymia: How are they Related? Comparing Two Versions of the Relational Answers Questionnaire Self-Presentation Strategies: A New Version of the Self-Presentation Scale The Continuum of Likeness Scales: A Proposal for Evaluating Self-identity Differentiation Updating the RC-Ecomap: A Multi-model, Theory-derived Instrument Advances in RC-Ecomap Research: Evaluating its Validity & Reliability A New Version of the Self-Other-Profile-Chart Unexpressed & Expressed Hurts: Two Different Trajectories for Similar Feelings Alexithymia Dimensions in Aging Alexithymia Dimensions & Perceived Emotional Parenting Styles Alexithymia Dimensions in Addiction Alexithymia Dimensions as Parenting Challenges Implications of Research on Alexithymia for Relational Competence Theory Index.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it