Social Justice and Career Development: Looking Back, Looking Forward
Bibliographic record
Abstract
Social justice has underpinned career development work since its inception. Over time however, while awareness of social justice issues has been retained, the focus of intervention has largely remained individual. Further, career theory has been criticised for its lack of attention to cultural influences such as gender, ethnicity, religion, socioeconomic status, and sexual orientation, in people's career development. In this regard, progress has been made to the extent that multicultural and diversity competencies have been identified and elaborated. However, such competencies maintain a predominant focus on interventions with individuals and there have been calls for career development to identify social justice competencies which necessarily suggest different roles and levels of intervention for career development practitioners. As the implications of globalisation become more apparent and societal inequity is perpetuated, it is timely to revisit the social justice origins of career development and consider how career development may position itself in the 21st century. This paper examines social justice in career development theory and practice, and considers implications for career development practitioners.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.011 | 0.022 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".