MétaCan
Menu
Back to cohort
Record W2336176313 · doi:10.1177/0894845316633524

Career Education at the Elementary School Level

2016· article· en· W2336176313 on OpenAlexaffabout
Annelise M. J. Welde, Kerry B. Bernes, Thelma M. Gunn, Stanley A. Ross

Bibliographic record

VenueJournal of Career Development · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsMainstreamCareer educationVariety (cybernetics)PsychologyMedical educationPsychological interventionPedagogyCareer developmentMathematics educationVocational educationPolitical scienceMedicine

Abstract

fetched live from OpenAlex

A teacher-training program was introduced in Southern Alberta, Canada, to enable intern teachers to integrate career education projects into their mainstream elementary school courses. This non-experimental, descriptive evaluation used content analysis to examine the effectiveness of 25 career education projects and their corresponding 56 types of career education interventions that were implemented by intern teachers. Twenty-five project reports and 555 student evaluation surveys were examined to determine trends in project strengths, challenges, and recommendations for career education. Students benefited from engaging in a variety of developmentally appropriate learning experiences that allowed them to engage in self-exploration and identify potential careers of interest. Implications for future research and practice are provided.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.283

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.062
GPT teacher head0.282
Teacher spread0.220 · 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 designNot applicable
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

Citations18
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Career DevelopmentSame topicCareer Development and DiversityFrench-language works237,207