Marketing graduate employability: understanding the tensions between institutional practice and external messaging
Bibliographic record
Abstract
Do the narratives of employability constructed by higher education institutions for marketing purposes differ from the conceptualisation and/or the realisation of employability within those institutions? The study reported here drew on interviews with 16 senior academic and student support staff who were tasked with developing student employability at one of nine institutions in Australia, Canada and the UK. We employed Holmes’ conceptions of employability as possessional, positional or processual to analyse how the interviewees conceptualised employability and the presentation of employability on the institutional websites. We found that most institutions’ employability marketing narratives were inconsistent with the institutional practice reported by staff. We explain this tension in the context of two competing characterisations of higher education: a university-student transaction view; and a learning view. We emphasise the need for internal and external narratives to align and advocate the need for engagement in a constructive and critical dialogue involving all stakeholders.
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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 | 0.022 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.037 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".