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Record W7097070293

Preparing Students for the Transition from College to Work

2016· article· en· W7097070293 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsEmployabilityPreparednessFocus groupWork (physics)Government (linguistics)StakeholderTransition (genetics)Higher education
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the perceived preparedness of college students for the transition from college to full-time employment. The study was concerned with the interest and rationale behind developing a required Exit Course for college students in order to improve the college to work transition. As well, possible content of an Exit Course was evaluated. The importance of addressing college to work transitions is highlighted by two phenomena. First, there are specific employability skills that employers in Canada are seeking in newly hired employees. Second, the provincial government in Ontario is determining college funding based on graduate employment statistics which are measured by graduate satisfaction, graduate employment, and employer satisfaction. The research concentrated on the following stakeholders involved in the transition from college to work: (a) current students, (b) recent graduates, (c) support staffwho assist students in college to work transition (Career Educators), and (d) employers. Through qualitative research, including focus groups and interviews, these stakeholder groups participated in the research to determine if the Exit Course was a viable solution to facilitate the transition from college to work. Focus groups were conducted with current students, while one-on-one, semi-structured interviews were conducted with recent graduates, Career Educators, and employers. Common themes elicited from the participants included the following: (a) although students were perceived by the participants of this study to be technically prepared for employment, they were perceived to have weak job search skills and i;^tlV:v:fA:J:U-^i»'*w'^'"'

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)0.007
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: Other · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.002
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 head0.040
GPT teacher head0.383
Teacher spread0.343 · 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
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
Published2016
Admission routes1
Has abstractyes

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