What perspectives underlie ‘researcher identity’? A review of two decades of empirical studies
Bibliographic record
Abstract
Abstract Over the past two decades, identity has emerged as a concept framing studies of early career researcher experience. Yet, identity is an amorphous concept, understood and used in a range of ways. This systematic review aimed to unpack the underpinnings of the notion of researcher identity. The final sample consisted of 38 empirical articles published in peer-reviewed journals in the last 20 years. Analyses focused on (a) identifying the dimensions used to define researcher identity, and (b) characterising the meta-theories—the underlying assumptions of the research—in relation to these dimensions. We identified four different stances towards researcher identity (clusters), based on variation on the identity dimensions in relation to the meta-theories. We characterised these as (1) transitioning among identities, (2) balancing identity continuity and change, (3) personal identity development through time and (4) personal and stable identity. These stances incorporate thought-provoking nuances and complex conceptualisations of the notion of researcher identity, for instance, that meta-theory was insufficient to characterise researcher identity stance. The contribution of the study is first to be able to differentiate four characterizations of researcher identity—important given that many studies had not clearly expressed a stance. The second is the potential of the four dimensions to help characterise identity, in past as well as future research—thus a useful tool for those working in this area. Many questions remain, but perhaps the biggest is to what extent and under what conditions is identity a productive notion for understanding early career researcher experience?
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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 | 0.085 | 0.192 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.036 | 0.035 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".