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Record W1629122071 · doi:10.3233/wor-2009-0857

Using metaphors to study occupational transitions: A case study of an injured worker with multiple chemical sensitivity

2009· article· en· W1629122071 on OpenAlexaff
Crystal Arnold, Lynn Shaw, Gerald Landry

Bibliographic record

VenueWork · 2009
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsCanada Auto WorkersWestern University
Fundersnot available
KeywordsSensitivity (control systems)Occupational exposureMedicineEnvironmental healthEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this case study was to explore transitions of an injured worker suffering from multiple chemical sensitivity (MCS), and his lived experiences in learning to function in everyday life with this injury. To date, little research exists about the transitions of a worker to an injured worker beyond the focus of strategies in returning to work and rehabilitation. METHODS: The injured worker's perspective was captured through the use of metaphors in understanding the transition processes of participating in daily life without work. Metaphors were used to facilitate this injured worker's expression of deep thoughts and feelings, and to allow for different and abstract ways of thinking about disability and illness. FINDINGS: Metaphors were identified within several transitions involved in the process of going from a worker to an injured worker functioning in daily life. CONCLUSIONS: The findings from this case study can be shared with others as a means of increasing the awareness of the experiences in managing daily life when living with MCS. In addition, insights from this injured worker's case could act as a venue for distributing knowledge about chemical injuries to health care professionals to broaden their views of this injury and its treatment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

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

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 head0.183
GPT teacher head0.511
Teacher spread0.328 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2009
Admission routes1
Has abstractyes

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