Attachment Issues 1 Rev 10/15/2009 COURSE TITLE: ATTACHMENT ISSUES IN CHILDREN: STRATEGIES & INTERVENTIONS NO. OF CREDITS: 3 QUARTER CREDITS WA CLOCK HRS: 27
Bibliographic record
Abstract
Many students who exhibit social skills deficits seem to lack an ability to effectively connect with other students as well as adults. The challenges faced by the average families and many school districts lend themselves to potential “high risk ” situations. Students who show a lack of remorse and inability to bond to others create a crisis within our school systems. This unique course will explain areas of attachment disorder, attachment theories and strategies to help educators become more successful with these high risk students. Topics such as defiance, fighting, passive-aggressive behaviors, stealing, lying, and aggression toward others will be discussed. Too often “basic ” behavioral strategies do not work well with this type of student. Through case studies, role play, and special speakers, each participant will become more adept and confident in working with the under-socialized child. This is a course designed for all educators, K-12. LEARNING OUTCOMES: As a result of taking this course, participants will learn how to: 1. Identify characteristics of those with emotional and behavioral challenges. 2. Recognize attachment deficits and their implications in society. 3. List effective interventions for students exhibiting minimal remorse toward behaviors. 4. Analyze case studies and identify causal factors of the behavior. 5. Develop a programmatic approach within the classroom (or school) that will benefit individual students and create a safe environment for others. 6. Incorporate strategies of social skills training within the context of their curriculum as it relates to attachment concepts. 7. Facilitate behavior and attitude change within a child that is feeling distant emotionally from others.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.468 | 0.162 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".