Bibliographic record
Abstract
First published in 1988. Child therapists have long been fascinated by children's human figure drawings and what they reveal about self-image, feelings, and' family relation ships. Now this comprehensively researched volume provides a valuable introduction to using children's human figure drawings as projective measures in a variety of settings. The principles for interpreting drawings, as well as general and specific indicators, are illustrated in 85 children's drawings. Part I on The Theory deals with the background of projective psychology, discussing art as a projective technique and emphasizing that all behavior, including drawings, reflects personality, attitudes and values. The authors examine the major methods of obtaining diagnostic information and recommend the use of several methods for best results. Part II on The Application examines in detail the projective use of children's human figure drawings to evaluate personality, relationships (particularly in families), group values, and attitudes. In each area, research is presented, directions for administration of various tests are given, and guidelines for interpretation are offered. Significant factors are revealed in numerous children's drawings, accompanied by clinical comments. Of special interest is the presentation of original research on group values among Canadian Indian (Saskatchewan Cree) children and on attitudes of young children toward teachers, doctors and other authority figures as revealed in human figure drawings. For psychologists, social workers, teachers and other child-care professionals, as well as students in these fields, this is an indispensable basic guide to interpreting human figure drawings.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.079 | 0.031 |
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".