Taking issue with how the Work-integrated Learning discourse ascribes a dualistic meaning to graduate employability
Bibliographic record
Abstract
Abstract Work-integrated Learning (WIL) is renowned for providing abridgebetween ‘theory’ and ‘practice’ that fosters ‘employable graduates’. This study critically argues that the WIL discourse continues to ascribe a dualistic meaning tograduate employabilitythat primarily contributes to creating the so-calledtheory–practice gapfor students. As an argument towards such a conclusion, a genealogical discourse analysis of how the graduate employability idea operates in 87 present and past official documents concerning the Cooperative Education (Co-op) WIL model is used. Two accounts of graduate employability, theantagonisticpractice acclaiming account and theharmonioustheory and practice account, recur in both the present and past documents. Both accounts contribute to creating the gap, while the latter also contributes to bridging it. The non-dualistic account, which involves knowing that the key to becoming employable is understanding how both research-based and informal theory shape daily occupational work, could be a useful alternative to these accounts. This is because it could encourage students to see how theory is a form of knowledge manifested in, rather than disconnected from, this work. However, the usual WIL design, whereby universities and workplaces outside universities are respectively institutionalised as the places where ‘theory’ and ‘practice’ is learnt, is not so much instrumental in spreading this non-dualistic account, but rather implies to students that ‘theory’ is absent from daily work until they apply it. Thus, I discuss how establishing physical and/or virtual countersites to the usual WIL design could potentially spread this account to students.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.051 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".