Performance in neo-liberal doctorates: the making of academics
Bibliographic record
Abstract
Purpose This study aims to better understand how academics-in-the-making construe doctoral performance and the impacts of this construal on their positioning in relation to doctoral performance expectations. Design/methodology/approach This study is based on 25 semi-structured interviews with PhD students from Canadian, Dutch, Scottish and Australian business schools. Findings Based on Decoteau’s (2016) concept of reflexive habitus, this study highlights how doctoral students’ construal is influenced by their previous experiences and by expectations from other adjacent fields in which they simultaneously gravitate. This leads them to adopt a position oscillating between resistance and compliance in relation to their understanding of doctoral performance expectations promoted in the academic field. Research limitations/implications The concept of reflexivity, as understood by Decoteau (2016), is found to be pivotal when an individual integrates into a new field. Practical implications This study encourages business schools to review expectations regarding doctoral performance. These expectations should be clear, but they should also leave room for PhD students to preserve their academic aspirations. Originality/value It is beneficial to empirically clarify the influence of performance expectations in academia on the reflexivity of PhD students, as the majority of studies exploring this topic mainly leverage auto-ethnographic data.
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 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 | 0.035 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.050 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".