Bibliographic record
Abstract
The book claims to be a ‘guidebook’—one that ‘practicum supervisors can refer to when issues or challenges arise’ (p. xiv) during the course of a practicum. It also claims to be the first ‘all-inclusive resource for training social work students in the field’. The edited book is written for the American market and would ultimately be intended for new field or practicum supervisors and, as such, it makes connections to the Council for Social Work Education (CSWE) (the regulatory body for social work education in the USA) requirements and expectations. The book is structured in a logical way, from initially thinking about working with a student in the practicum (placement), the process of working with the university, through to facilitating learning and providing appropriate educational opportunities, integrating theory with practice, assessment and working within the expected requirements, ending with ethical issues and dilemmas that may occur. As an entry-level book to prepare practitioners for the task of field education, the book has clear merit but I was rather frustrated at times by the lack of depth in some of the chapters—important issues did appear rather briefly dealt with, namely the chapters on learning, models of supervision and assessing students. The research referred to is also heavily USA-centric, although I did note key writers from Canada, namely Marian Bogo and colleagues (2007), as well as some key writers from the UK, such as Thompson (1995), Trevithick (2005) and Knott and Scragg (2010). As such, there is possibly a larger range of relevant international research that could have been utilised, such as the work of New Zealand social work academic Liz Beddoe and colleagues on supervision (see e.g. Davys and Beddoe (2010), Beddoe and Maidment (2015) and the work of British social work academics Mark Doel and Steven Shardlow (2005). On the other hand, as an entry-level book, the coverage appears to be satisfactory and the chapters provide helpful bibliographies. The strong focus on the US context therefore may reduce the contextual requirements for practicum supervisors working in other countries, but there were some interesting chapters that would have international relevance and applicability, such as Chapter 6 on integrating theory and practice methods in the field and Chapter 7 on supporting and developing students.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.022 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".