Essential Characteristics and Diagnostic Technique of Psychological Types of Love
Bibliographic record
Abstract
The paper is aimed at theoretical insight into phenomenology of psychological manifestations of love styles, identified by J. A. Lee, the Canadian sociologist, who used types of love described by ancient Greek philosophers as a basis for his classification. The author employs a number of aspects as the criteria for the analysis of essential characteristics of love styles: differentially expressed features of feelings, self-awareness, social perception, types of human relationships (suggested by J. L. Moreno and M. Buber), ways of realization of inward human nature (described by E. S. Fromm), level of sense of community and compensation mechanism for inferiority feeling (conceptualized by A. Adler). As a result of the theoretical study, the author outlined six psychological types of love: passionate love-admiration (eros), hedonistic love (ludus), love-friendship (storge), practical love (pragma), obsessive love (mania), altruistic love (agape). Theoretical representations of psychological types of love, formulated upon carrying out the phenomenological analysis, and application of substantive deductive construction strategy for psychological inventories enabled the author to design a diagnostic technique for psychological types of love. To test the technique, the author conducted the empirical study that involved 143 participants (89 women and 54 men) aged 18–32 (mean age = 22). The paper gives the reliability indicators for six scales of the diagnostic technique for the psychological types of love and the results of its convergent validation that prove good psychometric applicability of the designed psychodiagnostic tools and their differential diagnostic potential. The study revealed correlations of degree of psychological types of love with some sustainable personality traits (R. B. Cattell’s technique) and indicators of social and psychological adaptability.
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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 | 0.005 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".