KAJIAN CSR MELALUI SUDUT PANDANG PERENCANAAN TRANSAKTIF: STUDI KASUS PERENCANAAN CSR DI INDONESIA
Bibliographic record
Abstract
CSR gain local community development. However, its practice is contradictive, partially not only beneficial but also it does not bring significant benefits. CSR planning as an integration tool for the interest between corporate and local community is the main driving factor for its effectivity implementation. The article presents a communicative approach in CSR planning by combining both the concept of CSR and transactive planning. The general view that Corporate dominating CSR planning is the main criticism which causes its policy has not a significant impact. How is the conceptualization of CSR planning approach, which communicates with the beneficiary community, this article aims to reveal its understanding. The study evaluates the transactive process on CSR planning, through descriptive qualitative analysis of literature. The result proposes a CSR planning model based on transactive planning approach. The article also initiates that CSR planning is a transactive process which raised through knowledge transaction between planner and community toward towards legitimacy in increasing community support for company operations.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".