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Record W7029076287

Help Wanted: What Student Services Professionals Can Do to Help Post-Secondary Students and Recent Graduates with Disabilities Find Work

2020· article· en· W7029076287 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGerman Security and Defense Policies
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsWork (physics)Quality (philosophy)CurriculumWork experience
DOInot available

Abstract

fetched live from OpenAlex

T he increasing number of students with disabilities in our colleges and universities has resulted in large numbers of students and recent graduates with disabilities looking for meaningful employment.To better understand this trend, the Adaptech Research Network and the Quebec Association for Equity and Inclusion in Post-Secondary Education (AQEIPS) teamed up to conduct a two-phase pilot study wherein we carried out structured conversations with 10 professionals involved with student employment and distributed questionnaires to 25 students and recent graduates with disabilities who were currently employed.The goal of this study was to provide information for college professionals regarding what can -and should -be done to assist students and recent graduates with disabilities in their search for employment.Professionals we talked with include leaders of community disability organizations and specialized employment counsellors, as well as to campus-based disability service providers, employment counsellors, and career counsellors.We asked them who in their institution helps potential graduates with and without disabilities find jobs, who they believe should be doing this, what they think that students with disabilities want when it comes to employment services, what potential barriers students with disabilities face when seeking employment, and what has helped them get jobs.Students and recent graduates included 11 recent junior/community college graduates (9 females, 2 males) and 14 university students and recent graduates (6 females, 6 males, 2 agender or transgender).Participants' self-identified disabilities included, in descending order of frequency, mental illness, attention deficit hyperactivity disorder, learning disability, autism spectrum disorder, mobility impairment, blindness/low vision, limitation in use of hands/arms, chronic health problems, neurological impairment, and hearing impairment.We asked students and recent graduates how they found out about their present job; what helped them get their job; how long it took them to find their job; and if, when, and how they disclosed their disability.We also asked them what they thought that post-secondary professionals could do to help students and recent graduates with disabilities find a job.Students and recent graduates indicated that the following, in descending order, helped students with disabilities find out about job opportunities:• contacts/networking • employment websites • already working in the field • internship/co-op/apprenticeship • volunteering • campus professionals (employment counsellor, disability service provider, etc.) • community employment services • specialized disability related employment services As for what helped students actually get their jobs, students and recent graduates indicated the following, in descending order: • job skills • resumé/curriculum vitae (CV) • contacts/networking • academic credentials • interview skills

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)0.004
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0060.007
Open science0.0020.009
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0680.016

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 head0.032
GPT teacher head0.305
Teacher spread0.274 · 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

Citations0
Published2020
Admission routes1
Has abstractno

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