Bibliographic record
Abstract
Buku Akuntansi Keperilakuan menyajikan pendekatan interdisipliner dalam memahami praktik akuntansi modern yang tidak hanya dipengaruhi oleh angka dan data, tetapi juga oleh perilaku manusia. Buku ini menelusuri bagaimana faktor psikologis, sosial, dan budaya organisasi memengaruhi proses pencatatan, pelaporan, hingga pengambilan keputusan keuangan. Disusun dalam dua belas bab, buku ini mengupas berbagai topik penting mulai dari teori perilaku dalam akuntansi, pengaruh motivasi dan partisipasi dalam anggaran, peran sistem pengendalian manajemen, pengaruh budaya organisasi, hingga studi kasus akuntansi keperilakuan. Buku ini juga menyoroti bias-bias umum seperti overconfidence, anchoring, dan framing dalam praktik akuntansi, serta bagaimana teknologi dan regulasi terkini memengaruhi dinamika perilaku akuntan dan manajer keuangan.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.153 | 0.035 |
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".