Building global partnerships to study the occupational implications of long-term unemployment
Bibliographic record
Abstract
Occupational science is increasingly attending to how sociopolitical discourses and policies influence everyday occupation (Laliberte Rudman & Forwell, 2013). Given that occupational science is a global discipline, research must account for how such social forces differ across international contexts. This paper will highlight preliminary findings from a cross-national ethnographic pilot study of occupation during long-term unemployment. The pilot study took place at sister non-profit organizations that provided services to people who were unemployed in the United States and Canada. Each author generated data at one of the sites, beginning with informal (non-audio recorded) interviews with two to four front-line service providers (Lipsky, 2010) and repeated observations of group classes and individual client-provider meetings. Each author also conducted up to two 30 to 90-minute interviews with four service seekers from each site. All data generation occurred between March and November 2013 and included a total of 14 participants. Study data continues to be iteratively analyzed based on both critical discourse (Cheek, 2004) and situational (Clarke, 2005) analytic approaches.\nThis presentation will address how the topic of occupation manifested in individual service seeker interviews as well as interactions between service providers and service seekers at each site. Preliminary findings reveal that sociopolitical discourses overtly influenced provider-client interactions by constructing service seekers as ‘activated unemployed job seekers’ (Olsen, 2008) and idealizing particular occupations relative to such a construction. Discussion of these findings will attend to how service providers and service seekers framed the occupational implications of long-term unemployment in each study context. In particular, the discussion will focus on the imperatives of becoming work ready and procuring work, and how service seekers negotiated occupations relative to those imperatives in the United States and Canada.\nThis presentation will also describe the expansion of this pilot project into a larger interdisciplinary international study. Currently underway, this expansion aims to include marginalized sub-groups within the population of unemployed people, such as immigrants and people with criminal backgrounds. The presentation will close with two questions: 1) What is the potential of such work to illuminate contradictory social forces surrounding work and unemployment? 2) How can the study of occupation address and be used to rectify such contradictions for various groups in society?\nKey words: occupational science, cross-national research, unemployment
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.024 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".