A Comparison of Strengths and Interests Protocols in Career Assessment and Counseling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examined the relative performance of three career counseling protocols: a strengths-based protocol, an interest-based protocol, and a protocol that combined strengths and interests. Outcome measures included career exploration, occupational engagement, career decision self-efficacy, hope, positive and negative affect, and life satisfaction pre- and post-intervention. The participants consisted of 82 undergraduate students enrolled in a career and life-planning course. Each participant received a career counseling intervention and a Strong Interest Inventory (SII), StrengthsFinder, or both the SII and StrengthsFinder interpretation. While all three groups showed significant gains from pretest to posttest on most outcomes, results suggest the interests protocol (IP) was the most effective approach when considering the conservation of resources. However, results also merit further exploration of the combined protocol (CP; strengths plus interests) given the greatest gains were achieved by this approach on all but one construct, though not significantly different from the IP. Implications are discussed.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it