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Record W7046926474

Educational selection in Northwestern Ontario / by Peter B. Worrell. --

2017· other· en· W7046926474 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusEducational attainmentSelection (genetic algorithm)Educational institutionEducational researchPerspective (graphical)Higher educationPlan (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

The principal purpose of this study is to determine the degree to which the community college and university student populations are different with respect to socioeconomic composition.In addition to comparing the socioeconomic composition of the two populations, the study compares the two populations using a multitude of independent variables that have been theoretically proposed to effect levels of educational aspiration and post-secondary educational selection.A second reason for this study is to compare the two student populations regarding their general perspective of the labour market opportunity structure.Post-secondary candidates are now faced with the problem of a labour market condition which cannot sufficiently absorb postsecondary graduates, particularly those from the university (Canada Department of Manpower and Immigration, 1970; Harvey and Chamer, 1975; Harvey, 1979).The effect of this condition on levels of educational aspiration and educational selection is as yet unknown.A third reason for this study is to provide a variation in the approach to educational aspiration and/or educational selection research.Most status attainment studies have examined high school student populations in terms of what post-secondary institution they plan to attend as compared to actually observing the students in one.This study will examine students who have already realized the high school-held post-secondary school educational aspiration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.874
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.1960.001

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 head0.016
GPT teacher head0.246
Teacher spread0.230 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2017
Admission routes1
Has abstractyes

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