Operationalizing the good lives model: An examination of Holland's RIASEC theory and vocational congruence with offenders 2001--2008
Bibliographic record
Abstract
Lack of employment has been identified as a contributing factor to criminal behaviour (Andrews & Bonta, 2003). Canadian Correctional Services have responded accordingly through the provision of interventions directed toward addressing offender needs as they relate to employment issues. Nonetheless, critics have argued that intervention efforts are still largely based on the principles of risk reduction, with limited attention given to a theoretically integrated view of the rehabilitation process. Ward and Stewart (2003) proposed a "Good Lives" model of rehabilitation in hopes of moving toward an enhancement model rather than a strictly harm avoidance model. "Good lives" (Ward & Stewart, 2003) are referred to as methods of living that are beneficial and fulfilling for individuals, and it is argued that any conception of a possible "good life" should take note of an offender's capabilities, temperament, interests, skills, values and support networks. The current research operationalized a 'good lives' model by exploring the theoretical construct of vocational congruence as a protective factor, leading to greater success within correctional environments and upon release in the community. Two studies explored the relevance of Holland's theory of vocational personalities and work environments (1997) for offender populations. The first study examined the validity of Holland's RIASEC Structure for a convenience sample of 305 federally sentenced offenders. Three RIASEC models (i.e., Holland, 1997; Gati, 1982; Round & Tracey, 1996) were also examined in Study I. Results indicated that two of these models are valid for an offender population. The second study examined Holland's theory of vocational congruence (1997) with a convenience sample of 304 federally sentenced offenders. Results revealed minimal support for the statistical significance of vocational congruence for this sample of offenders. Nevertheless, post-hoc analyses showed interesting differences for Aboriginal and women offenders, as well as offenders over 30 years of age. Furthermore, vocational congruence emerged as a significant factor in predicting time to recidivism. The role of behavioural adaptability and relevance of career counselling are introduced. Theoretical and operational implications, as well as implications for the 'Good Lives' model are discussed. The author argues for the value of continued research regarding Holland's RIASEC typology and vocational congruence with offender populations.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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 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".