Examining how former Employment Ontario Second Career participants perceive the phenomenon of meaningful employment
Bibliographic record
Abstract
Evidence has shown that one can have meaningful work but not be meaningfully employed. Meaningful work (work that provides social value) and meaningful employment (the conditions of employment) are often conflated in the workforce development sector; however, while related, these concepts are distinct. This thesis examines how former Second Career participants who have engaged in Employment Ontario’s (EO) academic retraining initiatives perceive the phenomenon of meaningful employment. Former Second Career participants were chosen for this study because the Second Career program (a government policy intervention) claimed to help recipients find stable, meaningful employment. However, there is a lack of clarity on what meaningful employment constitutes. This thesis, therefore, argues that the conflation between meaningful work and meaningful employment serves the interests of neoliberal institutions, hence abdicating their responsibility for providing robust worker protections. Furthermore, this conflation ultimately undermines the interests of workers—specifically low-wage workers. The research utilizes the tenets of intersectionality and counternarratives within critical race theory (CRT) and draws on interviews with ten former Second Career participants. As a Christian researcher, I also highlighted the debates between CRT and Christian social justice to demonstrate the commonalities and nuances they offer in evaluating and addressing systemic injustice. These interviews were, however, solely analyzed from a CRT lens in accordance with the interpretive phenomenological design adopted for this study. The participants’ accounts reveal that present-day socioeconomic and political issues have influenced their understanding of meaningful employment. For instance, their experiences illustrate how living at the convergence of multiple intersecting identities (e.g., race, class, language, gender, citizenship, etc.) amplify systemic marginalization in a racialized labour market. Additionally, this research also counters the normative view that academic upgrading, adequate skills and hard work are a definitive pathway to achieving meaningful employment. Overall, this thesis highlights the importance of examining whose interests are served by the conflation of meaningful work and meaningful employment. The concealment of our deeper understanding of meaningful employment serves to alleviate the government’s responsibility for protecting all workers, thus further exacerbating labour market inequities. My hope is that this study will help to catalyze future theoretical development of this phenomenon to help critically assess the real needs and concerns of those most impacted by policy interventions. Additionally, this study contributes to the growth of research examining the perspectives of participants who have engaged in EO’s retraining initiatives.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".