A <scp>quarter‐century review of HRM in small and medium‐sized enterprises</scp>: <scp>Capturing what we know</scp>, <scp>exploring where we need to go</scp>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Despite the proliferation of HRM research, only a small fraction explores the context of small and medium‐sized enterprises (SMEs). Where HRM in SMEs has received attention, the literature base remains fragmented and variable, comprising a plurality of definitions, explanations, and methods. To advance understanding, this paper uses a quarter‐century systematic review drawing on an evidence base of 137 peer‐reviewed articles. A cumulative framework is presented capturing key developments and synthesizing existing areas of research focus. Analysis of limitations and knowledge‐gaps finds a failure to differentiate across various types of SMEs, limited appreciation of SME characteristics and contextual conditions, and a dominance of managerial perspectives. An agenda for future research on HRM in SMEs is outlined with respect to definitional parameters, HR practices, HRM–performance, key determinants, and presenting issues. The paper concludes that SMEs offer a unique, fruitful, and timely context for investigations of HRM.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it