Privilege and Belonging
Bibliographic record
Abstract
In this rejoinder, we advance the dialogue stimulated by our major contribution (Smith et al., 2012) in which we present the findings from a survey of early career professionals (ECPs) in Division 17, the Society of Counseling Psychology. We respond to the reactants’ concerns and observations using the lenses of privilege and belonging to guide our response. Building from the premise that the Society needs to continue to create and sustain efforts to attract and retain burgeoning counseling psychologists—including faculty members, practitioners, and those whose careers have combined or unique foci—we offer additional suggestions toward meeting the goal of expanding the richness of membership to include a wide array of those who identify with the premises of the Society and the specialty of counseling psychology. The importance of mentoring for advanced students and ECPs with an array of career trajectories is particularly emphasized.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.074 |
| Scholarly communication | 0.011 | 0.025 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.008 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 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".