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Record W2407540468 · doi:10.1177/002234090105500105

The Hamilton SPE Evaluation Tool (HSET): Is it Any Good?

2001· article· en· W2407540468 on OpenAlexaff
Thomas St. James O’Connor, Elizabeth Meakes, Lori Edey, Marlene Healey-Ogden, Glenn Empey, Sarah Klimek, Kathleen O’Neill

Bibliographic record

VenueJournal of Pastoral Care · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsContext (archaeology)Strengths and weaknessesAccreditationTriangulationUnit (ring theory)SociologyPsychologySocial psychologyMathematics educationMedical educationGeographyCartographyMedicine

Abstract

fetched live from OpenAlex

Presents the Hamilton Supervised Pastoral Evaluation Tool (HSET). HSET is a self-report that evaluates student learning in a basic SPE unit utilizing six areas: supervisory relationship, personal growth, professional growth, theological reflection, learning context, and overall growth. Reviews statistics involving seven regional units consisting of 18 SPE units with 101 students. Utilizes methodological, investigator, and data triangulation by drawing on qualitative study and CAPPE accreditation review. Discusses strengths and weaknesses of HSET and makes recommendations for further use.

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)0.029
metaresearch head score (Gemma)0.096
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: none
Teacher disagreement score0.029
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.096
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.054
GPT teacher head0.402
Teacher spread0.348 · 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

Citations7
Published2001
Admission routes1
Has abstractyes

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