Introduction to School Social Work
Bibliographic record
Abstract
Introduction to School Social WorkA Definitive Guide for Empowering Students, Families, and SchoolsStep into the dynamic world of school social work with this essential and comprehensive resource designed for MSW students, educators, and practicing school social workers. Introduction to School Social Work brings together the theory, skills, legal knowledge, and real-world strategies needed to support student well-being in today’s diverse and challenging school environments.What You’ll Learn:<br>From foundational principles to advanced intervention methods, this book covers the full spectrum of school social work. Every chapter is crafted to support both academic understanding and field application, making it an ideal companion for coursework, practicum, and professional practice.Key Highlights Include:1. Comprehensive syllabus-aligned content for MSW programs2. Global legal frameworks – U.S., Canada, EU, Australia, and India3. Detailed coverage of child and adolescent issues – substance abuse, bullying, suicide, learning disabilities, and more4. Theoretical foundations: Ecological Systems, CBT, Attachment, and more5. Practical intervention strategies – counseling, group work, life skills education6. Ready-to-use tools – genograms, sociograms, case reports, crisis response7. Support system insights – mental health resources, NGOs, tech integrationIdeal For:1. MSW students and educators2. School counselors and mental health professionals3. Teachers and school administrators4. Social work interns and field supervisors5. Anyone committed to child protection and school well-beingWhy This Book?<br>In an era where schools are ground zero for emotional, psychological, and social issues, this book is your complete roadmap. Empower your practice with a resource that is inclusive, legally informed, student-centered, and rooted in both compassion and evidence.
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 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.397 | 0.007 |
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; both teacher heads 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".