The Impact of Information Technology Evolution on the Forms of Knowledge in Public Sector Social Work: Examples from Canada and the UK
Bibliographic record
Abstract
In recent years, governments have been enthusiastic about the potential of digital changes to transform the way the public sector operates. While such changes were originally found to deprioritize the forms of knowledge needed by UK child protection workers, instead favouring administrative forms of knowledge, it was not known whether this impact was similar in other liberal democracies, nor whether this simply represented a phase in the evolution of digital government. This study explored this question through desk research and by interviewing and observing social workers as they interacted with a new information system. The study’s findings suggest that while the experiences of social workers in a Canadian province replicate the previous UK experience, current digital changes in the UK that are built on the earlier foundation may enhance the knowledge of child protection workers. These findings suggest that forms of knowledge may evolve with technological change.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.006 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; 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".