Professional socialization and prudence strategies
Bibliographic record
Abstract
This article explores the increasing use of social media, particularly Facebook groups, by social workers for professional socialization and support. Social media platforms are used individually to promote services and develop professional identities, and collectively for knowledge sharing, mutual support, and critical reflection. The study focuses on Quebec social workers, examining their use of Facebook groups to connect, share experiences, and reduce work-related stress. Data were collected from a private Facebook group, posts within the group, and interviews with 14 social workers. The analysis identified three main action logics behind group usage: integration (community belonging), utility (finding tools and information), and subjectivation (questioning practices) (Jauréguiberry & Proulx, 2011). The study found that social workers use these groups primarily outside working hours for professional practice discussions, personal opinions, social mobilization, and job-related posts. Prudence emerged as a key theme, with participants exercising caution to protect their psychological well-being and professional reputation. Facebook groups serve as important spaces for professional socialization, offering support and resources while requiring careful navigation to avoid potential risks.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".