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Record W2136385538 · doi:10.22230/ijepl.2008v3n5a70

A Study of Counselors' Legal Challenges and Their Perceptions of Their Ability to Respond

2008· article· en· W2136385538 on OpenAlexvenueno aff
Debra G. Leggett, Theodore P. Remley

Bibliographic record

VenueInternational Journal of Education Policy and Leadership · 2008
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsnot available
Fundersnot available
KeywordsCertificationLicensurePerceptionMedical educationPsychologyEngineering ethicsMedicinePolitical scienceLawEngineering

Abstract

fetched live from OpenAlex

The authors explore the results of a study that assessed the types and frequency of legal issues encountered by counselors and counselors’ perceptions of their ability to respond to these issues. They also assessed whether the participants’ perceptions were related to practice setting, years of experience, completion of a course in ethics, recent completion of continuing education in ethics or legal issues, state licensure status, certification by the National Board of Certified Counselors (NBCC), and highest degree earned. Results demonstrate that counselors feel most prepared to deal with situations encountered most often, but that school counselors do not feel as prepared to face most ethical and legal issues.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.050
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.209
GPT teacher head0.419
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2008
Admission routes1
Has abstractyes

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