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Record W1849782806

Exploring the Help-Seeking Attitudes of Graduate Students at an Off-Campus Site

2010· article· en· W1849782806 on OpenAlexvenueno aff
John T. McCarthy, Michelle L. Bruno, C.A. Sherman

Bibliographic record

VenueCanadian Journal of Counselling and Psychotherapy · 2010
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsnot available
Fundersnot available
KeywordsGraduate studentsMedical educationDescriptive statisticsHelp-seekingPsychologySample (material)Descriptive researchFamily medicineMedicineMental healthPsychiatrySociology
DOInot available

Abstract

fetched live from OpenAlex

This study examined the help-seeking attitudes of graduate students enrolled in an off-campus professional centre. The sample consisted of 217 participants enrolled in 10 graduate programs (130 women [60%], 37 men [17%], 50 unspecified [23%]). Analyses (descriptive statistics and t-tests) indicated that women possessed more favourable at-titudes toward seeking counselling than men. Furthermore, an overwhelming majority of graduate students would not travel to the main campus to utilize counselling services. Many participants identified potential obstacles, including lack of time, affordability, and lack of insurance coverage, as important obstacles to help-seeking. Several factors were also found to be significant predictors of help-seeking attitudes. University counselling centre professionals are encouraged to be available and sensitive to the counselling needs of off-campus graduate students.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.104
GPT teacher head0.343
Teacher spread0.239 · 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 designQualitative
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

Citations6
Published2010
Admission routes1
Has abstractyes

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