MétaCan
Menu
Back to cohort
Record W2727689093 · doi:10.5539/jel.v6n4p175

Counselor Perceptions: Let Us Do Our Job!

2017· article· en· W2727689093 on OpenAlexvenueno aff
Stephen Benigno

Bibliographic record

VenueJournal of Education and Learning · 2017
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsnot available
Fundersnot available
KeywordsRealmPsychologyPerceptionJob satisfactionPedagogyMedical educationSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Elementary and Middle school administrators continually struggle with developing instructional programs that will address the academic and human developmental levels of the students in their care. Addressing the human development and the academic issues related to the elementary and middle school student is only a small percentage of the attention required for that student. Many students at the elementary and middle school levels encounter issues related to social and emotional development that are often overwhelming and many times detrimental to the academic development of those students. School administrators address those issues by utilizing the existing infrastructure of the schools. One of the key components of the school infrastructure is the school counselor. In some situations, school counselors are being required to perform duties outside the realm of their perceived responsibilities. This study was conducted to ascertain school counselor perceptions with respect to job performance, expectations, satisfaction and responsibility. The results of the study indicated that the counselors involved in the study believed that they are being required to perform duties outside the realm of their responsibilities and that the performance of these duties has an impact on their effectiveness as school counselors.

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)0.003
metaresearch head score (Gemma)0.011
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.002
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.039
GPT teacher head0.411
Teacher spread0.372 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Education and LearningSame topicCounseling Practices and SupervisionFrench-language works237,207